{"paragraphs":[{"title":"Import python libraries and display settings","text":"%python\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport oml\nimport inspect \n\npd.set_option('display.max_rows', 500)\npd.set_option('display.max_columns', 500)\npd.set_option('display.width', 1000)","user":"JIE","dateUpdated":"2021-08-03T14:19:58+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_-1900401537","id":"20210803-141850_84641886","dateCreated":"2021-03-31T19:18:01+0000","dateStarted":"2021-08-03T14:19:59+0000","dateFinished":"2021-08-03T14:19:59+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"focus":true,"$$hashKey":"object:40"},{"title":"Obtain a proxy object to the Customer Insurance Life Time Value table ","text":"%python\n\nCUST_DF = oml.sync(schema = 'JIE', table = 'CUSTOMER_INSURANCE_LTV')\n","user":"JIE","dateUpdated":"2021-07-26T18:35:08+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_-1053451974","id":"20210803-141850_1044107528","dateCreated":"2021-03-31T19:18:43+0000","dateStarted":"2021-07-26T18:35:08+0000","dateFinished":"2021-07-26T18:35:10+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:41"},{"title":"Pick a subset of the columns","text":"%python\n\nCUST_DF = CUST_DF[['CUSTOMER_ID','MARITAL_STATUS', 'STATE', 'GENDER', 'PROFESSION', 'REGION', 'CREDIT_BALANCE', 'LTV_BIN', 'MORTGAGE_AMOUNT', 'BANK_FUNDS', 'NUM_DEPENDENTS', 'INCOME', 'CREDIT_CARD_LIMITS', 'BUY_INSURANCE']]\n","user":"JIE","dateUpdated":"2021-07-12T20:03:53+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_-1092808268","id":"20210803-141850_631232618","dateCreated":"2021-03-31T19:23:22+0000","dateStarted":"2021-07-12T20:03:54+0000","dateFinished":"2021-07-12T20:03:54+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:42"},{"title":"Overview of the dataset","text":"%python\n\nz.show(CUST_DF.head())","user":"JIE","dateUpdated":"2021-07-12T20:03:56+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{"0":{"graph":{"mode":"table","height":300,"optionOpen":false,"setting":{"table":{"tableGridState":{"columns":[{"name":"MARITAL_STATUS","visible":true,"width":173,"sort":{},"filters":[{}],"pinned":""},{"name":"STATE","visible":true,"width":150,"sort":{},"filters":[{}],"pinned":""},{"name":"CUSTOMER_ID","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"GENDER","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"REGION","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"PROFESSION","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"CREDIT_BALANCE","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"LTV_BIN","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"INCOME","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"CREDIT_CARD_LIMITS","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"MORTGAGE_AMOUNT","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"BANK_FUNDS","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"BUY_INSURANCE","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""},{"name":"NUM_DEPENDENTS","visible":true,"width":"*","sort":{},"filters":[{}],"pinned":""}],"scrollFocus":{},"selection":[],"grouping":{"grouping":[],"aggregations":[],"rowExpandedStates":{}},"treeView":{},"pagination":{"paginationCurrentPage":1,"paginationPageSize":250}},"tableColumnTypeState":{"names":{"CUSTOMER_ID":"string","MARITAL_STATUS":"string","STATE":"string","GENDER":"string","PROFESSION":"string","REGION":"string","CREDIT_BALANCE":"string","LTV_BIN":"string","MORTGAGE_AMOUNT":"string","BANK_FUNDS":"string","NUM_DEPENDENTS":"string","INCOME":"string","CREDIT_CARD_LIMITS":"string","BUY_INSURANCE":"string"},"updated":false},"tableOptionSpecHash":"[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]","tableOptionValue":{"useFilter":false,"showPagination":false,"showAggregationFooter":false},"updated":false,"initialized":false}},"commonSetting":{}}}},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TABLE","data":"CUSTOMER_ID\tMARITAL_STATUS\tSTATE\tGENDER\tPROFESSION\tREGION\tCREDIT_BALANCE\tLTV_BIN\tMORTGAGE_AMOUNT\tBANK_FUNDS\tNUM_DEPENDENTS\tINCOME\tCREDIT_CARD_LIMITS\tBUY_INSURANCE\nCU1900 \tSINGLE\tNY \tM \tIT Staff\tNorthEast\t0\tMEDIUM\t0\t0\t0\t62789\t900\tNo\nCU1901 \tDIVORCED\tMI \tF \tPROF-62\tMidwest\t0\tLOW\t4000\t3900\t6\t87333\t4000\tNo\nCU1902 \tMARRIED\tNY \tM \tAdministrator\tNorthEast\t0\tMEDIUM\t1000\t13825\t3\t63010\t900\tNo\nCU1903 \tMARRIED\tNY \tF \tAuthor\tNorthEast\t0\tMEDIUM\t1500\t0\t5\t65261\t800\tNo\nCU1904 \tDIVORCED\tOK \tF \tWaiter/Waitress\tMidwest\t0\tHIGH\t3000\t251\t3\t60975\t500\tNo\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_-1898390174","id":"20210803-141850_1204588226","dateCreated":"2021-03-31T19:21:39+0000","dateStarted":"2021-07-12T20:03:57+0000","dateFinished":"2021-07-12T20:03:58+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:43"},{"title":"Recode the flag variable BUY_INSURANCE for convenience","text":"%python\n\nCUST_DF = CUST_DF.replace(old = ['Yes'], new = [1.0], default = 0.0, columns = ['BUY_INSURANCE'])\n","user":"JIE","dateUpdated":"2021-07-12T20:04:00+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_592641626","id":"20210803-141850_517781277","dateCreated":"2021-04-01T20:17:33+0000","dateStarted":"2021-07-12T20:04:01+0000","dateFinished":"2021-07-12T20:04:02+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:44"},{"title":"Save the subset table","text":"%python\n\ntry:\n oml.drop(table = 'CUST_SUBSET_TBL')\nexcept:\n print(\"No such table\")\nCUST_SUBSET_DF = CUST_DF.materialize(table = 'CUST_SUBSET_TBL')","user":"JIE","dateUpdated":"2021-07-12T20:04:03+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_-174357287","id":"20210803-141850_2123339359","dateCreated":"2021-04-01T18:59:47+0000","dateStarted":"2021-07-12T20:04:04+0000","dateFinished":"2021-07-12T20:04:06+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:45"},{"title":"Get the proxy object for the subset table","text":"%python\n\nCUST_SUBSET_DF = oml.sync(table = 'CUST_SUBSET_TBL')","user":"JIE","dateUpdated":"2021-07-29T18:11:46+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_-2051878791","id":"20210803-141850_629693804","dateCreated":"2021-04-01T19:19:31+0000","dateStarted":"2021-07-29T18:11:46+0000","dateFinished":"2021-07-29T18:11:47+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:46"},{"title":"Check the table values attached","text":"%python\n\nz.show(CUST_SUBSET_DF.head().round(4))","user":"JIE","dateUpdated":"2021-07-29T18:12:12+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{"0":{"graph":{"mode":"table","height":300,"optionOpen":false,"setting":{"table":{"tableGridState":{},"tableColumnTypeState":{"names":{"CUSTOMER_ID":"string","MARITAL_STATUS":"string","STATE":"string","GENDER":"string","PROFESSION":"string","REGION":"string","CREDIT_BALANCE":"string","LTV_BIN":"string","MORTGAGE_AMOUNT":"string","BANK_FUNDS":"string","NUM_DEPENDENTS":"string","INCOME":"string","CREDIT_CARD_LIMITS":"string","BUY_INSURANCE":"string"},"updated":false},"tableOptionSpecHash":"[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]","tableOptionValue":{"useFilter":false,"showPagination":false,"showAggregationFooter":false},"updated":false,"initialized":false}},"commonSetting":{}}}},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TABLE","data":"CUSTOMER_ID\tMARITAL_STATUS\tSTATE\tGENDER\tPROFESSION\tREGION\tCREDIT_BALANCE\tLTV_BIN\tMORTGAGE_AMOUNT\tBANK_FUNDS\tNUM_DEPENDENTS\tINCOME\tCREDIT_CARD_LIMITS\tBUY_INSURANCE\nCU13000 \tSINGLE\tNV \tM \tDBA\tSouthwest\t0\tMEDIUM\t0\t0\t2\t75578\t1500\t0\nCU10448 \tMARRIED\tIL \tF \tDBA\tMidwest\t0\tMEDIUM\t1200\t0\t5\t63431\t1000\t0\nCU11965 \tMARRIED\tNY \tF \tDBA\tNorthEast\t0\tHIGH\t1200\t0\t5\t75017\t1500\t0\nCU8030 \tMARRIED\tFL \tM \tDBA\tSouth\t0\tMEDIUM\t1400\t0\t3\t67715\t1000\t0\nCU12655 \tMARRIED\tNY \tM \tDBA\tNorthEast\t0\tMEDIUM\t1600\t0\t3\t62675\t1000\t0\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_1592066344","id":"20210803-141850_2106476033","dateCreated":"2021-03-31T19:32:37+0000","dateStarted":"2021-07-29T18:12:13+0000","dateFinished":"2021-07-29T18:12:14+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:47"},{"title":"Create 10-Fold CV datasets. Save the train and test dataset as a view for the record","text":"%python\n\nDF = oml.sync(table = 'CUST_SUBSET_TBL')\n\nfold = 10\npairs = DF.KFold(n_splits = fold, strata_cols = ['BUY_INSURANCE'])\n\n","user":"JIE","dateUpdated":"2021-08-03T14:27:46+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_666258891","id":"20210803-141850_2133924481","dateCreated":"2021-06-30T20:36:22+0000","dateStarted":"2021-08-03T14:27:47+0000","dateFinished":"2021-08-03T14:27:50+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:48"},{"title":"Check the content of the output","text":"%python\n\nprint(type(pairs))\nprint(len(pairs))\ntype(pairs[0])","user":"JIE","dateUpdated":"2021-07-28T17:03:53+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"\n10\n\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_2136844295","id":"20210803-141850_414538550","dateCreated":"2021-07-27T20:10:56+0000","dateStarted":"2021-07-28T17:02:56+0000","dateFinished":"2021-07-28T17:02:56+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:49"},{"title":"Train dataset in first fold","text":"%python\n\nprint(pairs[0][0].shape)\nz.show(pairs[0][0].head())","user":"JIE","dateUpdated":"2021-07-28T17:04:44+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{"0":{"graph":{"mode":"table","height":300,"optionOpen":false,"setting":{"table":{"tableGridState":{},"tableColumnTypeState":{"names":{"CUSTOMER_ID":"string","MARITAL_STATUS":"string","STATE":"string","GENDER":"string","PROFESSION":"string","REGION":"string","CREDIT_BALANCE":"string","LTV_BIN":"string","MORTGAGE_AMOUNT":"string","BANK_FUNDS":"string","NUM_DEPENDENTS":"string","INCOME":"string","CREDIT_CARD_LIMITS":"string","BUY_INSURANCE":"string"},"updated":false},"tableOptionSpecHash":"[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]","tableOptionValue":{"useFilter":false,"showPagination":false,"showAggregationFooter":false},"updated":false,"initialized":false}},"commonSetting":{}}},"1":{"graph":{"mode":"table","height":300,"optionOpen":false,"setting":{"table":{"tableGridState":{},"tableColumnTypeState":{"names":{"CUSTOMER_ID":"string","MARITAL_STATUS":"string","STATE":"string","GENDER":"string","PROFESSION":"string","REGION":"string","CREDIT_BALANCE":"string","LTV_BIN":"string","MORTGAGE_AMOUNT":"string","BANK_FUNDS":"string","NUM_DEPENDENTS":"string","INCOME":"string","CREDIT_CARD_LIMITS":"string","BUY_INSURANCE":"string"},"updated":false},"tableOptionSpecHash":"[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]","tableOptionValue":{"useFilter":false,"showPagination":false,"showAggregationFooter":false},"updated":false,"initialized":false}},"commonSetting":{}}}},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"(12523, 14)\n"},{"type":"TABLE","data":"CUSTOMER_ID\tMARITAL_STATUS\tSTATE\tGENDER\tPROFESSION\tREGION\tCREDIT_BALANCE\tLTV_BIN\tMORTGAGE_AMOUNT\tBANK_FUNDS\tNUM_DEPENDENTS\tINCOME\tCREDIT_CARD_LIMITS\tBUY_INSURANCE\nCU11965 \tMARRIED\tNY \tF \tDBA\tNorthEast\t0\tHIGH\t1200\t0\t5\t75017\t1500\t0\nCU10297 \tMARRIED\tCA \tM \tDBA\tWest\t0\tHIGH\t1700\t0\t3\t69822\t800\t0\nCU13599 \tDIVORCED\tOR \tM \tDBA\tWest\t0\tMEDIUM\t2300\t0\t3\t65811\t1000\t0\nCU15609 \tDIVORCED\tNY \tM \tDBA\tNorthEast\t0\tHIGH\t2300\t0\t3\t75068\t1500\t0\nCU1922 \tDIVORCED\tNY \tM \tDBA\tNorthEast\t0\tHIGH\t2900\t0\t0\t58815\t900\t0\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_1765429396","id":"20210803-141850_365248708","dateCreated":"2021-07-27T20:11:34+0000","dateStarted":"2021-07-28T17:04:42+0000","dateFinished":"2021-07-28T17:04:43+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:50"},{"title":"Test dataset in first fold","text":"%python\n\nprint(pairs[0][1].shape)\nz.show(pairs[0][1].head())","user":"JIE","dateUpdated":"2021-07-28T17:04:48+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{"0":{"graph":{"mode":"table","height":300,"optionOpen":false,"setting":{"table":{"tableGridState":{},"tableColumnTypeState":{"names":{"CUSTOMER_ID":"string","MARITAL_STATUS":"string","STATE":"string","GENDER":"string","PROFESSION":"string","REGION":"string","CREDIT_BALANCE":"string","LTV_BIN":"string","MORTGAGE_AMOUNT":"string","BANK_FUNDS":"string","NUM_DEPENDENTS":"string","INCOME":"string","CREDIT_CARD_LIMITS":"string","BUY_INSURANCE":"string"},"updated":false},"tableOptionSpecHash":"[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]","tableOptionValue":{"useFilter":false,"showPagination":false,"showAggregationFooter":false},"updated":false,"initialized":false}},"commonSetting":{}}},"1":{"graph":{"mode":"table","height":300,"optionOpen":false,"setting":{"table":{"tableGridState":{},"tableColumnTypeState":{"names":{"CUSTOMER_ID":"string","MARITAL_STATUS":"string","STATE":"string","GENDER":"string","PROFESSION":"string","REGION":"string","CREDIT_BALANCE":"string","LTV_BIN":"string","MORTGAGE_AMOUNT":"string","BANK_FUNDS":"string","NUM_DEPENDENTS":"string","INCOME":"string","CREDIT_CARD_LIMITS":"string","BUY_INSURANCE":"string"},"updated":false},"tableOptionSpecHash":"[{\"name\":\"useFilter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable filter for columns\"},{\"name\":\"showPagination\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable pagination for better navigation\"},{\"name\":\"showAggregationFooter\",\"valueType\":\"boolean\",\"defaultValue\":false,\"widget\":\"checkbox\",\"description\":\"Enable a footer for displaying aggregated values\"}]","tableOptionValue":{"useFilter":false,"showPagination":false,"showAggregationFooter":false},"updated":false,"initialized":false}},"commonSetting":{}}}},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"(1357, 14)\n"},{"type":"TABLE","data":"CUSTOMER_ID\tMARITAL_STATUS\tSTATE\tGENDER\tPROFESSION\tREGION\tCREDIT_BALANCE\tLTV_BIN\tMORTGAGE_AMOUNT\tBANK_FUNDS\tNUM_DEPENDENTS\tINCOME\tCREDIT_CARD_LIMITS\tBUY_INSURANCE\nCU13000 \tSINGLE\tNV \tM \tDBA\tSouthwest\t0\tMEDIUM\t0\t0\t2\t75578\t1500\t0\nCU10448 \tMARRIED\tIL \tF \tDBA\tMidwest\t0\tMEDIUM\t1200\t0\t5\t63431\t1000\t0\nCU8030 \tMARRIED\tFL \tM \tDBA\tSouth\t0\tMEDIUM\t1400\t0\t3\t67715\t1000\t0\nCU12655 \tMARRIED\tNY \tM \tDBA\tNorthEast\t0\tMEDIUM\t1600\t0\t3\t62675\t1000\t0\nCU3440 \tMARRIED\tCA \tM \tDBA\tWest\t0\tHIGH\t1500\t1000\t1\t67853\t1300\t0\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_649920465","id":"20210803-141850_443855411","dateCreated":"2021-07-27T20:12:30+0000","dateStarted":"2021-07-28T17:04:46+0000","dateFinished":"2021-07-28T17:04:47+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:51"},{"title":"Create view from OML data frame","text":"%python\n\nfor i, pair in enumerate(pairs):\n\n train_view_name = 'CUST_TRAIN_V_'\n test_view_name = 'CUST_TEST_V_'\n train_view_name += str(i+1)\n test_view_name += str(i+1)\n\n try:\n oml.drop(view = train_view_name)\n oml.drop(view = test_view_name)\n except:\n print(\"No such view\")\n\n _ = pair[0].create_view(view = train_view_name)\n _ = pair[1].create_view(view = test_view_name)\n print(train_view_name)\n print(test_view_name)","user":"JIE","dateUpdated":"2021-07-28T17:05:31+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"interrupted":false,"jobName":"paragraph_1628000330915_-305850268","id":"20210803-141850_1843807982","dateCreated":"2021-07-27T20:10:54+0000","status":"READY","progressUpdateIntervalMs":500,"commited":false,"$$hashKey":"object:52"},{"title":"Display one of the train set","text":"%sql\nselect * from 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\tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t64670\t1500\t0\nCU10038 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t58705\t1500\t0\nCU10147 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t6\t65111\t700\t0\nCU10218 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t66009\t1000\t0\nCU10278 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t60893\t1500\t0\nCU10283 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t60802\t800\t0\nCU10304 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t66344\t800\t0\nCU10310 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t58382\t1500\t0\nCU10311 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t0\t0\t0\t73113\t1500\t0\nCU10392 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t2\t65197\t700\t0\nCU10518 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t66533\t800\t0\nCU10556 \tSINGLE\tWI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t66564\t1500\t0\nCU10565 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t59200\t1500\t0\nCU10566 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t69578\t1500\t0\nCU10569 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t58439\t800\t0\nCU10582 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t1\t69729\t1500\t0\nCU10650 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t68364\t700\t0\nCU1108 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t0\t0\t1\t61853\t600\t0\nCU11139 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t0\t3\t60615\t1000\t0\nCU11183 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tLOW\t0\t0\t0\t73533\t1500\t0\nCU11184 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t0\t0\t66295\t1500\t0\nCU11185 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t82088\t2500\t0\nCU11186 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tLOW\t0\t0\t0\t51424\t2500\t0\nCU11188 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t0\t58901\t1500\t0\nCU11191 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t0\t0\t57840\t1000\t0\nCU11196 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t62295\t1500\t0\nCU11283 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t0\t0\t72208\t1500\t0\nCU11426 \tSINGLE\tOR \tM \tNurse\tWest\t0\tLOW\t0\t0\t6\t68253\t1000\t0\nCU11647 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t0\t0\t65609\t1500\t0\nCU11864 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t65410\t1000\t0\nCU12396 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t65694\t1000\t0\nCU12451 \tSINGLE\tNV \tM \tNurse\tSouthwest\t0\tMEDIUM\t0\t0\t2\t61262\t1000\t0\nCU12522 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t61912\t1000\t0\nCU12559 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t3\t62411\t700\t0\nCU12761 \tSINGLE\tMS \tM \tNurse\tSouth\t0\tLOW\t0\t0\t0\t64895\t1500\t0\nCU1299 \tSINGLE\tUT \tM \tNurse\tSouthwest\t0\tLOW\t0\t0\t0\t66266\t1500\t0\nCU13165 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t3\t64926\t1000\t0\nCU13351 \tSINGLE\tUT \tM \tNurse\tSouthwest\t0\tLOW\t0\t0\t0\t67786\t1500\t0\nCU13473 \tSINGLE\tMN \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t63186\t700\t0\nCU1361 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t0\t0\t0\t60530\t900\t0\nCU13806 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t3\t70404\t1000\t0\nCU13874 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t62150\t700\t0\nCU13976 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t6\t67836\t600\t0\nCU14174 \tSINGLE\tUT \tM \tNurse\tSouthwest\t0\tLOW\t0\t0\t0\t68487\t1500\t0\nCU14239 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t3\t59882\t600\t0\nCU14406 \tSINGLE\tOR \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t64574\t700\t0\nCU14689 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t0\t3\t60204\t1000\t0\nCU14832 \tSINGLE\tOR \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t66821\t1000\t0\nCU1505 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t59830\t900\t0\nCU15154 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t65871\t1000\t0\nCU15164 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t62149\t700\t0\nCU15327 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t64793\t1000\t0\nCU15608 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t71826\t1000\t0\nCU1724 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t70169\t1500\t0\nCU1952 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t0\t0\t68315\t1500\t0\nCU197 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t0\t0\t0\t73461\t2500\t0\nCU408 \tSINGLE\tOR \tM \tNurse\tWest\t0\tLOW\t0\t0\t3\t61730\t900\t0\nCU4429 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t59564\t1000\t0\nCU4453 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t65679\t700\t0\nCU4487 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t0\t0\t62555\t1100\t0\nCU5207 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t68367\t1500\t0\nCU6019 \tSINGLE\tDC \tM \tNurse\tNorthEast\t0\tHIGH\t0\t0\t0\t66117\t700\t0\nCU6261 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t60157\t600\t0\nCU6418 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t59296\t600\t0\nCU6444 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t58661\t1500\t0\nCU6462 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t0\t62404\t1000\t0\nCU6492 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t0\t61950\t1200\t0\nCU6497 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t0\t57178\t1000\t0\nCU6557 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t60804\t900\t0\nCU6577 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t62797\t1400\t0\nCU6594 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t0\t0\t0\t70756\t900\t0\nCU6625 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t65768\t900\t0\nCU6634 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t0\t0\t0\t69576\t900\t0\nCU6649 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t57802\t900\t0\nCU6667 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t63574\t900\t0\nCU6694 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t58019\t900\t0\nCU6837 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t55592\t1500\t0\nCU6841 \tSINGLE\tNC \tM \tNurse\tSouth\t0\tMEDIUM\t0\t0\t1\t67426\t600\t0\nCU6846 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t61085\t800\t0\nCU686 \tSINGLE\tUT \tM \tNurse\tSouthwest\t0\tLOW\t0\t0\t0\t65701\t1000\t0\nCU6861 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t0\t58294\t1000\t0\nCU6862 \tSINGLE\tWI \tM \tNurse\tMidwest\t0\tHIGH\t0\t0\t0\t76658\t1500\t0\nCU6885 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t0\t0\t0\t75118\t1500\t0\nCU6903 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t65769\t900\t0\nCU6946 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t0\t0\t0\t73930\t1500\t0\nCU7017 \tSINGLE\tMN \tM \tNurse\tWest\t0\tLOW\t0\t0\t0\t69961\t900\t0\nCU7103 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t65837\t900\t0\nCU7107 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t67617\t900\t0\nCU7134 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t63581\t900\t0\nCU7135 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t66803\t900\t0\nCU7136 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t0\t0\t0\t69859\t900\t0\nCU7137 \tSINGLE\tNV \tM \tNurse\tSouthwest\t0\tMEDIUM\t0\t0\t0\t67749\t900\t0\nCU7149 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t0\t57946\t1000\t0\nCU7185 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t65723\t1500\t0\nCU7187 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t58036\t1500\t0\nCU7217 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t55930\t1500\t0\nCU7235 \tSINGLE\tMN \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t64042\t1500\t0\nCU7256 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t69237\t900\t0\nCU7260 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t70668\t1500\t0\nCU7262 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t57296\t1500\t0\nCU7269 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t70884\t1500\t0\nCU7285 \tSINGLE\tNC \tM \tNurse\tSouth\t0\tHIGH\t0\t0\t0\t69539\t1500\t0\nCU7305 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t70889\t1500\t0\nCU7321 \tSINGLE\tMO \tM \tNurse\tMidwest\t0\tLOW\t0\t0\t0\t59909\t1500\t0\nCU7647 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t0\t75076\t1500\t0\nCU7839 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t59621\t700\t0\nCU7954 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t65772\t1000\t0\nCU7999 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t68778\t700\t0\nCU8023 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tLOW\t0\t0\t3\t61013\t1000\t0\nCU8421 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t0\t71814\t1200\t0\nCU8422 \tSINGLE\tUT \tM \tNurse\tSouthwest\t0\tLOW\t0\t0\t0\t70424\t1500\t0\nCU8481 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t3\t64914\t1000\t0\nCU8507 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t64399\t1000\t0\nCU8535 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t66165\t1500\t0\nCU8605 \tSINGLE\tMN \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t2\t58557\t1500\t0\nCU8713 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t68589\t700\t0\nCU8728 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t2\t59083\t700\t0\nCU8782 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t69051\t1500\t0\nCU8783 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t3\t64090\t1500\t0\nCU8784 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t63807\t800\t0\nCU8948 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t0\t0\t0\t67561\t700\t0\nCU8950 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t3\t65729\t700\t0\nCU9018 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t71001\t1500\t0\nCU9029 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t64242\t1500\t0\nCU9045 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t63723\t800\t0\nCU9065 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t0\t0\t0\t61291\t800\t0\nCU9069 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t71405\t1500\t0\nCU9159 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tLOW\t0\t0\t3\t63938\t1000\t0\nCU9211 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t60260\t700\t0\nCU9244 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t1\t60980\t700\t0\nCU9311 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t62483\t800\t0\nCU9526 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t0\t0\t58017\t800\t0\nCU9547 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t0\t0\t0\t76781\t1500\t0\nCU9551 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t0\t0\t62170\t1500\t0\nCU9556 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t0\t0\t0\t62591\t800\t0\nCU9561 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t0\t57627\t1500\t0\nCU9679 \tSINGLE\tNV \tM \tNurse\tSouthwest\t0\tMEDIUM\t0\t0\t0\t59906\t1000\t0\nCU9792 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t59139\t1500\t0\nCU9823 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t73850\t1500\t0\nCU9825 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t0\t0\t66482\t1500\t0\nCU9934 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tLOW\t0\t0\t3\t65768\t1000\t0\nCU9936 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t0\t3\t68371\t700\t0\nCU9991 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t0\t6\t67537\t700\t0\nCU10393 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t200\t0\t4\t68416\t700\t0\nCU11636 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t200\t0\t3\t68548\t1000\t0\nCU12954 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t200\t0\t3\t61767\t1000\t0\nCU14528 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t200\t0\t3\t67422\t1000\t0\nCU9176 \tSINGLE\tNC \tM \tNurse\tSouth\t0\tHIGH\t200\t0\t1\t58687\t700\t0\nCU9902 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t200\t0\t1\t65602\t700\t0\nCU9992 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t200\t0\t3\t58089\t1000\t0\nCU10886 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t300\t0\t3\t58809\t1000\t0\nCU11876 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tVERY HIGH\t300\t0\t1\t66018\t700\t0\nCU13487 \tSINGLE\tIL \tM \tNurse\tMidwest\t0\tHIGH\t300\t0\t1\t65739\t1000\t0\nCU11886 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t400\t0\t3\t60646\t1000\t0\nCU13612 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t400\t0\t3\t61781\t1000\t0\nCU7221 \tSINGLE\tWA \tM \tNurse\tWest\t0\tVERY HIGH\t400\t0\t0\t70362\t1500\t0\nCU9663 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t400\t0\t3\t61616\t1000\t0\nCU10695 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t500\t0\t1\t64992\t700\t0\nCU11887 \tSINGLE\tFL \tM \tNurse\tSouth\t0\tHIGH\t500\t0\t3\t70760\t1000\t0\nCU12674 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t500\t0\t3\t62780\t1000\t0\nCU13464 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t500\t0\t3\t64958\t700\t0\nCU13501 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t500\t0\t3\t60430\t700\t0\nCU13584 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t500\t0\t6\t60293\t1000\t0\nCU6853 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t500\t0\t3\t69833\t800\t0\nCU9993 \tMARRIED\tMN \tF \tNurse\tWest\t0\tHIGH\t700\t0\t2\t65265\t700\t0\nCU8937 \tMARRIED\tNC \tM \tNurse\tSouth\t0\tHIGH\t800\t0\t3\t62140\t700\t0\nCU10422 \tMARRIED\tCA \tM \tNurse\tWest\t0\tHIGH\t1000\t0\t3\t71433\t1000\t0\nCU6708 \tMARRIED\tCA \tM \tNurse\tWest\t0\tVERY HIGH\t1000\t0\t0\t58331\t900\t0\nCU9873 \tMARRIED\tMI \tF \tNurse\tMidwest\t0\tHIGH\t1000\t0\t1\t65416\t800\t0\nCU10853 \tMARRIED\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t1200\t0\t3\t63194\t700\t0\nCU7129 \tMARRIED\tNY \tM \tNurse\tNorthEast\t0\tVERY HIGH\t1300\t0\t0\t66207\t900\t0\nCU6406 \tMARRIED\tCA \tM \tNurse\tWest\t0\tHIGH\t1500\t0\t0\t65855\t1500\t0\nCU6640 \tMARRIED\tNY \tM \tNurse\tNorthEast\t0\tVERY HIGH\t1500\t0\t0\t70678\t900\t0\nCU6823 \tMARRIED\tMI \tM \tNurse\tMidwest\t0\tVERY HIGH\t1500\t0\t0\t67727\t1100\t0\nCU7155 \tMARRIED\tMI \tM \tNurse\tMidwest\t0\tHIGH\t1500\t0\t0\t62025\t900\t0\nCU1929 \tDIVORCED\tNY \tM \tNurse\tNorthEast\t0\tLOW\t2000\t0\t0\t66712\t500\t0\nCU6398 \tDIVORCED\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t2500\t0\t0\t57440\t1500\t0\nCU7272 \tDIVORCED\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t2500\t0\t0\t71795\t1500\t0\nCU194 \tDIVORCED\tMI \tM \tNurse\tMidwest\t0\tHIGH\t3000\t0\t1\t63103\t500\t0\nCU5319 \tDIVORCED\tCA \tM \tNurse\tWest\t0\tVERY HIGH\t3000\t0\t0\t69742\t900\t0\nCU7297 \tDIVORCED\tNY \tM \tNurse\tNorthEast\t0\tLOW\t3000\t0\t0\t71582\t1000\t0\nCU11129 \tDIVORCED\tOH \tM \tNurse\tMidwest\t0\tHIGH\t4000\t0\t2\t60688\t1000\t0\nCU12740 \tDIVORCED\tCA \tM \tNurse\tWest\t0\tHIGH\t4000\t0\t4\t65302\t2000\t0\nCU6676 \tDIVORCED\tMI \tM \tNurse\tMidwest\t0\tHIGH\t4000\t0\t0\t69051\t900\t0\nCU8916 \tDIVORCED\tDC \tM \tNurse\tNorthEast\t0\tHIGH\t4000\t0\t2\t64367\t1000\t0\nCU6645 \tDIVORCED\tCA \tM \tNurse\tWest\t0\tHIGH\t4500\t0\t0\t64197\t900\t0\nCU7118 \tDIVORCED\tCA \tM \tNurse\tWest\t0\tHIGH\t4500\t0\t0\t68721\t900\t0\nCU9530 \tWIDOWED\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t5000\t0\t0\t61893\t800\t0\nCU5559 \tMARRIED\tMS \tM \tNurse\tSouth\t0\tVERY HIGH\t8000\t0\t0\t58978\t1000\t0\nCU7127 \tWIDOWED\tNV \tM \tNurse\tSouthwest\t0\tHIGH\t10000\t0\t0\t69224\t900\t0\nCU10891 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t135\t0\t3\t61195\t700\t0\nCU14809 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t135\t0\t3\t60780\t1000\t0\nCU11885 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t150\t0\t3\t70389\t1000\t0\nCU12468 \tSINGLE\tMS \tM \tNurse\tSouth\t0\tMEDIUM\t150\t0\t3\t70355\t1000\t0\nCU9944 \tSINGLE\tWI \tM \tNurse\tMidwest\t0\tHIGH\t150\t0\t3\t59272\t1000\t0\nCU12452 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t160\t0\t4\t64361\t700\t0\nCU14707 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t160\t0\t3\t58321\t1000\t0\nCU10143 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t170\t0\t1\t62996\t700\t0\nCU14676 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t174\t0\t3\t63013\t1000\t0\nCU12770 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t177\t0\t3\t61812\t1000\t0\nCU8982 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t190\t0\t3\t60395\t1000\t0\nCU9995 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t195\t0\t3\t66495\t1000\t0\nCU7974 \tSINGLE\tFL \tM \tNurse\tSouth\t0\tHIGH\t205\t0\t3\t64028\t1000\t0\nCU13898 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t220\t0\t3\t62992\t1000\t0\nCU14915 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t220\t0\t1\t69276\t1000\t0\nCU9392 \tSINGLE\tMN \tM \tNurse\tWest\t0\tHIGH\t224\t0\t3\t71354\t1000\t0\nCU12846 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tVERY HIGH\t225\t0\t1\t67798\t600\t0\nCU12325 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t228\t0\t3\t73067\t1500\t0\nCU14807 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t240\t0\t3\t57545\t1000\t0\nCU10686 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t250\t0\t3\t61996\t700\t0\nCU8325 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t250\t0\t3\t67008\t1000\t0\nCU11900 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t252\t0\t3\t64317\t700\t0\nCU14107 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t252\t0\t3\t58778\t1000\t0\nCU14140 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t259\t0\t1\t59948\t700\t0\nCU12619 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t260\t0\t6\t61346\t600\t0\nCU14783 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t260\t0\t3\t57281\t1000\t0\nCU15367 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t279\t0\t3\t64717\t700\t0\nCU8493 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t310\t0\t3\t68872\t1000\t0\nCU13966 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t330\t0\t1\t59743\t600\t0\nCU10361 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t350\t0\t0\t58896\t800\t0\nCU10014 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t351\t0\t3\t60423\t1000\t0\nCU7132 \tSINGLE\tCA \tM \tNurse\tWest\t0\tVERY HIGH\t360\t0\t0\t68659\t900\t0\nCU7164 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t360\t0\t0\t61644\t900\t0\nCU10410 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t380\t0\t3\t64415\t1000\t0\nCU9962 \tSINGLE\tAL \tM \tNurse\tSouth\t0\tHIGH\t390\t0\t3\t60890\t700\t0\nCU6698 \tSINGLE\tCA \tM \tNurse\tWest\t0\tVERY HIGH\t396\t0\t0\t65574\t900\t0\nCU7940 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t403\t0\t3\t66045\t1000\t0\nCU11122 \tSINGLE\tMN \tM \tNurse\tWest\t0\tHIGH\t450\t0\t3\t59996\t1000\t0\nCU8716 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tVERY HIGH\t450\t0\t3\t62848\t700\t0\nCU14120 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t473\t0\t3\t63748\t700\t0\nCU6434 \tSINGLE\tUT \tM \tNurse\tSouthwest\t0\tHIGH\t503\t0\t0\t62438\t900\t0\nCU8138 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t510\t0\t3\t70992\t1000\t0\nCU9545 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t520\t0\t0\t62809\t900\t0\nCU10564 \tSINGLE\tNY \tM \tNurse\tNorthEast\t4258\tHIGH\t546\t0\t0\t70996\t1500\t0\nCU11868 \tSINGLE\tNC \tM \tNurse\tSouth\t0\tVERY HIGH\t570\t0\t1\t67992\t700\t0\nCU10140 \tMARRIED\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t780\t0\t3\t71888\t1500\t0\nCU7317 \tMARRIED\tCA \tM \tNurse\tWest\t0\tHIGH\t910\t0\t0\t59923\t900\t0\nCU7106 \tMARRIED\tCA \tM \tNurse\tWest\t0\tHIGH\t1178\t0\t0\t60714\t900\t0\nCU9564 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t300\t0\t57482\t1500\t0\nCU9657 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t400\t0\t74399\t1500\t0\nCU7220 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t800\t0\t63993\t1500\t0\nCU15304 \tMARRIED\tCA \tM \tNurse\tWest\t0\tHIGH\t1500\t900\t2\t57803\t1000\t0\nCU7276 \tSINGLE\tIL \tM \tNurse\tMidwest\t591\tHIGH\t200\t1100\t0\t64223\t1500\t0\nCU6588 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tLOW\t0\t1200\t4\t60915\t700\t0\nCU9761 \tMARRIED\tNY \tM \tNurse\tNorthEast\t7458\tHIGH\t1500\t1400\t1\t58906\t1000\t0\nCU11195 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t1500\t0\t73390\t2500\t1\nCU4981 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t1500\t0\t66258\t900\t0\nCU7251 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t450\t1600\t0\t69773\t1500\t1\nCU5147 \tMARRIED\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t1500\t1700\t0\t68185\t900\t1\nCU9512 \tDIVORCED\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t4800\t2200\t1\t55424\t3500\t0\nCU7302 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t0\t2400\t0\t68973\t1200\t0\nCU10863 \tOTHER\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t15000\t4000\t5\t49506\t4000\t0\nCU11189 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t4100\t0\t64222\t1500\t0\nCU7101 \tMARRIED\tMI \tM \tNurse\tMidwest\t0\tHIGH\t1751\t6300\t0\t69128\t900\t0\nCU7284 \tWIDOWED\tCA \tF \tNurse\tWest\t0\tHIGH\t10000\t8000\t0\t66173\t800\t1\nCU4386 \tSINGLE\tCA \tM \tNurse\tWest\t33249\tMEDIUM\t0\t9200\t0\t66097\t600\t0\nCU6388 \tMARRIED\tNY \tF \tNurse\tNorthEast\t0\tVERY HIGH\t5000\t9300\t0\t82099\t3500\t1\nCU9533 \tSINGLE\tMI \tM \tNurse\tMidwest\t134\tHIGH\t0\t9400\t0\t66963\t800\t0\nCU14039 \tSINGLE\tMO \tM \tNurse\tMidwest\t0\tLOW\t0\t250\t3\t61187\t1000\t0\nCU10433 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t397\t250\t3\t57896\t1000\t1\nCU14121 \tSINGLE\tMS \tM \tNurse\tSouth\t0\tHIGH\t660\t250\t3\t65496\t1000\t1\nCU9943 \tMARRIED\tIL \tM \tNurse\tMidwest\t0\tHIGH\t800\t450\t3\t61611\t700\t1\nCU2340 \tMARRIED\tMI \tM \tNurse\tMidwest\t0\tVERY HIGH\t950\t601\t0\t74283\t1600\t0\nCU7245 \tDIVORCED\tMI \tM \tNurse\tMidwest\t0\tHIGH\t2000\t901\t0\t73006\t1500\t1\nCU10562 \tMARRIED\tNY \tM \tNurse\tNorthEast\t0\tVERY HIGH\t1050\t901\t0\t62257\t1500\t0\nCU6757 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t1333\t3\t63371\t1000\t0\nCU896 \tSINGLE\tCA \tM \tNurse\tWest\t56065\tHIGH\t0\t1652\t0\t69955\t800\t0\nCU7288 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t1656\t0\t67674\t600\t0\nCU10850 \tMARRIED\tCA \tM \tNurse\tWest\t0\tVERY HIGH\t1137\t1660\t1\t66135\t700\t1\nCU6877 \tSINGLE\tCA \tM \tNurse\tWest\t0\tLOW\t0\t1769\t0\t70376\t1000\t0\nCU4405 \tSINGLE\tNV \tM \tNurse\tSouthwest\t0\tMEDIUM\t0\t1898\t0\t63438\t600\t1\nCU7189 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t0\t1950\t0\t64003\t900\t1\nCU3147 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tHIGH\t0\t1956\t0\t71740\t2500\t0\nCU6745 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t2056\t0\t64836\t900\t0\nCU6643 \tMARRIED\tMN \tM \tNurse\tWest\t19540\tHIGH\t5000\t2201\t0\t69219\t1100\t1\nCU10537 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t0\t2256\t0\t74471\t1500\t0\nCU3606 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t2328\t0\t62663\t800\t0\nCU4575 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t2420\t0\t61553\t500\t1\nCU6461 \tSINGLE\tNY \tM \tNurse\tNorthEast\t52355\tMEDIUM\t0\t2733\t0\t68116\t700\t0\nCU3438 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t3001\t0\t60194\t900\t0\nCU7254 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t3187\t0\t73432\t1500\t0\nCU400 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t3333\t0\t60752\t700\t0\nCU6831 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t3866\t0\t59786\t700\t0\nCU6015 \tSINGLE\tMN \tM \tNurse\tWest\t0\tHIGH\t0\t4001\t0\t65833\t1500\t0\nCU6481 \tMARRIED\tCA \tM \tNurse\tWest\t38588\tHIGH\t1600\t4103\t3\t71859\t1400\t0\nCU7156 \tDIVORCED\tMN \tM \tNurse\tWest\t0\tHIGH\t2500\t4150\t0\t60797\t1000\t0\nCU4287 \tSINGLE\tCA \tM \tNurse\tWest\t0\tMEDIUM\t0\t4219\t0\t64199\t700\t0\nCU6832 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t4363\t0\t62582\t800\t0\nCU6661 \tDIVORCED\tNY \tM \tNurse\tNorthEast\t0\tHIGH\t2000\t4440\t0\t64698\t900\t1\nCU2547 \tDIVORCED\tMI \tM \tNurse\tMidwest\t65453\tHIGH\t3000\t4741\t0\t58164\t1300\t0\nCU7320 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t4849\t0\t62077\t800\t0\nCU6934 \tSINGLE\tNY \tM \tNurse\tNorthEast\t26870\tMEDIUM\t0\t5045\t0\t60096\t1000\t0\nCU5997 \tDIVORCED\tCA \tM \tNurse\tWest\t2980\tVERY HIGH\t2000\t5240\t0\t64065\t900\t0\nCU1887 \tSINGLE\tCA \tM \tNurse\tWest\t42378\tMEDIUM\t0\t5470\t0\t64124\t800\t0\nCU6254 \tSINGLE\tMI \tM \tNurse\tMidwest\t0\tLOW\t0\t6385\t6\t67639\t700\t0\nCU5991 \tDIVORCED\tCA \tM \tNurse\tWest\t8777\tHIGH\t2800\t6568\t0\t66938\t900\t0\nCU1885 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t6608\t1\t76843\t1600\t1\nCU6829 \tSINGLE\tCA \tM \tNurse\tWest\t15287\tMEDIUM\t0\t6622\t0\t60340\t1200\t0\nCU7154 \tDIVORCED\tNY \tM \tNurse\tNorthEast\t28\tHIGH\t3000\t7168\t0\t67686\t1000\t1\nCU669 \tDIVORCED\tMI \tM \tNurse\tMidwest\t0\tHIGH\t2200\t7390\t1\t68882\t1500\t0\nCU4783 \tMARRIED\tCA \tM \tNurse\tWest\t11797\tVERY HIGH\t8500\t8045\t0\t66090\t500\t0\nCU6992 \tSINGLE\tCA \tM \tNurse\tWest\t0\tHIGH\t0\t11000\t0\t71500\t2500\t0\nCU6998 \tSINGLE\tIL \tM \tNurse\tMidwest\t0\tMEDIUM\t0\t11500\t0\t68631\t1400\t0\nCU6819 \tSINGLE\tNY \tM \tNurse\tNorthEast\t0\tMEDIUM\t0\t13400\t0\t65427\t1300\t0\nCU6269 \tDIVORCED\tMI \tM \tNurse\tMidwest\t0\tHIGH\t4500\t15000\t0\t60342\t3500\t1\nCU9973 \tMARRIED\tCA \tM \tNurse\tWest\t0\tVERY HIGH\t5000\t18400\t0\t63368\t900\t0\nCU1266 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tHIGH\t0\t0\t0\t63099\t700\t0\nCU1302 \tSINGLE\tFL \tM \tAuthor\tSouth\t0\tHIGH\t0\t0\t0\t60983\t500\t0\nCU15620 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tLOW\t0\t0\t6\t61394\t600\t0\nCU1597 \tSINGLE\tNY \tM \tAuthor\tNorthEast\t0\tLOW\t0\t0\t0\t68100\t1700\t0\nCU1599 \tSINGLE\tMI \tM \tAuthor\tMidwest\t0\tHIGH\t0\t0\t0\t66428\t700\t0\nCU1634 \tSINGLE\tCO \tM \tAuthor\tWest\t0\tLOW\t0\t0\t3\t56317\t1500\t0\nCU2081 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tHIGH\t0\t0\t0\t60442\t700\t0\nCU3086 \tSINGLE\tNY \tM \tAuthor\tNorthEast\t0\tMEDIUM\t0\t0\t3\t67338\t1500\t0\nCU3517 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tLOW\t0\t0\t0\t74103\t1500\t0\nCU4420 \tSINGLE\tMI \tM \tAuthor\tMidwest\t0\tLOW\t0\t0\t0\t67971\t1500\t0\nCU5180 \tSINGLE\tMI \tM \tAuthor\tMidwest\t0\tHIGH\t0\t0\t0\t64562\t900\t0\nCU5579 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tMEDIUM\t0\t0\t0\t60514\t1300\t0\nCU6014 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tLOW\t0\t0\t0\t58343\t1000\t0\nCU6223 \tSINGLE\tUT \tM \tAuthor\tSouthwest\t4280\tMEDIUM\t0\t0\t1\t63583\t700\t0\nCU635 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tMEDIUM\t0\t0\t0\t68557\t900\t0\nCU6353 \tSINGLE\tNY \tM \tAuthor\tNorthEast\t0\tLOW\t0\t0\t0\t61104\t1600\t0\nCU6465 \tSINGLE\tCA \tM \tAuthor\tWest\t782\tMEDIUM\t0\t0\t3\t70343\t900\t0\nCU664 \tSINGLE\tMI \tM \tAuthor\tMidwest\t0\tMEDIUM\t0\t0\t3\t66601\t600\t0\nCU6682 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tLOW\t0\t0\t0\t66798\t900\t0\nCU7065 \tDIVORCED\tCA \tM \tAuthor\tWest\t175268\tLOW\t0\t0\t3\t71630\t1500\t0\nCU7649 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tLOW\t0\t0\t0\t66137\t1300\t0\nCU9818 \tSINGLE\tNY \tM \tAuthor\tNorthEast\t0\tMEDIUM\t0\t0\t3\t76743\t1500\t0\nCU890 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tMEDIUM\t700\t0\t6\t58704\t700\t0\nCU15613 \tMARRIED\tCA \tF \tAuthor\tWest\t0\tMEDIUM\t800\t0\t6\t65530\t600\t0\nCU1090 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tVERY HIGH\t1000\t0\t0\t55139\t2500\t0\nCU1390 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tVERY HIGH\t1000\t0\t1\t60102\t1200\t0\nCU563 \tMARRIED\tCA \tM \tAuthor\tWest\t61209\tLOW\t1000\t0\t1\t64608\t900\t0\nCU6871 \tMARRIED\tCA \tF \tAuthor\tWest\t0\tMEDIUM\t1100\t0\t3\t56137\t1500\t0\nCU1479 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tMEDIUM\t1200\t0\t4\t56221\t1600\t0\nCU6771 \tMARRIED\tOR \tM \tAuthor\tWest\t0\tMEDIUM\t1200\t0\t4\t61697\t1500\t0\nCU13853 \tMARRIED\tNC \tF \tAuthor\tSouth\t0\tMEDIUM\t1300\t0\t6\t67684\t700\t0\nCU5822 \tMARRIED\tMI \tF \tAuthor\tMidwest\t0\tHIGH\t1300\t0\t6\t62312\t1700\t0\nCU12820 \tMARRIED\tOR \tM \tAuthor\tWest\t0\tVERY HIGH\t1500\t0\t1\t60720\t1000\t0\nCU1903 \tMARRIED\tNY \tF \tAuthor\tNorthEast\t0\tMEDIUM\t1500\t0\t5\t65261\t800\t0\nCU634 \tMARRIED\tMI \tM \tAuthor\tMidwest\t661\tLOW\t1500\t0\t0\t60959\t900\t0\nCU2405 \tMARRIED\tMI \tM \tAuthor\tMidwest\t0\tHIGH\t1800\t0\t1\t59978\t1000\t0\nCU2165 \tSINGLE\tMI \tF \tAuthor\tMidwest\t0\tVERY HIGH\t618\t0\t1\t65690\t500\t0\nCU8238 \tMARRIED\tOR \tF \tAuthor\tWest\t0\tHIGH\t1117\t0\t1\t60740\t1000\t0\nCU11353 \tMARRIED\tNY \tM \tAuthor\tNorthEast\t0\tHIGH\t1256\t0\t3\t72353\t1500\t0\nCU2177 \tMARRIED\tNY \tM \tAuthor\tNorthEast\t0\tHIGH\t1530\t0\t0\t65768\t900\t0\nCU12450 \tDIVORCED\tMI \tM \tAuthor\tMidwest\t0\tHIGH\t2150\t0\t1\t59933\t1000\t0\nCU11495 \tMARRIED\tCA \tF \tAuthor\tWest\t0\tHIGH\t1000\t300\t1\t61086\t1000\t1\nCU6337 \tMARRIED\tNY \tM \tAuthor\tNorthEast\t0\tHIGH\t750\t400\t3\t63792\t700\t0\nCU14806 \tMARRIED\tMI \tM \tAuthor\tMidwest\t0\tHIGH\t700\t500\t3\t68004\t700\t0\nCU14187 \tMARRIED\tCA \tF \tAuthor\tWest\t0\tVERY HIGH\t1000\t500\t1\t73407\t2500\t1\nCU15602 \tMARRIED\tFL \tM \tAuthor\tSouth\t0\tHIGH\t1000\t500\t1\t61290\t1000\t1\nCU6500 \tMARRIED\tCA \tF \tAuthor\tWest\t0\tHIGH\t1700\t500\t1\t54560\t1500\t0\nCU10165 \tMARRIED\tNV \tM \tAuthor\tSouthwest\t62272\tHIGH\t1000\t600\t3\t60684\t700\t0\nCU7669 \tMARRIED\tCA \tF \tAuthor\tWest\t0\tVERY HIGH\t1100\t700\t4\t85664\t2500\t0\nCU2961 \tMARRIED\tMI \tM \tAuthor\tMidwest\t0\tHIGH\t1000\t800\t3\t74251\t1600\t0\nCU6491 \tMARRIED\tMI \tM \tAuthor\tMidwest\t0\tHIGH\t1100\t800\t4\t56092\t1500\t0\nCU6489 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tHIGH\t963\t1000\t3\t68171\t700\t0\nCU13863 \tMARRIED\tMI \tF \tAuthor\tMidwest\t0\tVERY HIGH\t1200\t1100\t1\t58697\t700\t1\nCU5754 \tSINGLE\tCA \tM \tAuthor\tWest\t34134\tLOW\t0\t1200\t0\t68358\t1000\t0\nCU12956 \tMARRIED\tNY \tF \tAuthor\tNorthEast\t0\tHIGH\t1000\t1200\t1\t68207\t1000\t0\nCU1401 \tDIVORCED\tCA \tF \tAuthor\tWest\t0\tHIGH\t2000\t1200\t1\t72669\t1500\t1\nCU3447 \tDIVORCED\tNY \tF \tAuthor\tNorthEast\t0\tHIGH\t3000\t1200\t1\t63673\t800\t0\nCU15214 \tMARRIED\tMI \tF \tAuthor\tMidwest\t0\tLOW\t1180\t1200\t1\t71437\t1000\t0\nCU9889 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tMEDIUM\t1000\t1400\t3\t71366\t1500\t1\nCU5171 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tMEDIUM\t1500\t1400\t4\t55666\t1700\t0\nCU5545 \tSINGLE\tMI \tM \tAuthor\tMidwest\t0\tLOW\t0\t1500\t0\t61509\t1000\t0\nCU2408 \tDIVORCED\tNY \tF \tAuthor\tNorthEast\t23525\tHIGH\t2000\t1500\t1\t70986\t1000\t0\nCU667 \tMARRIED\tMI \tF \tAuthor\tMidwest\t0\tHIGH\t1350\t1500\t2\t71232\t1500\t0\nCU9779 \tMARRIED\tNY \tM \tAuthor\tNorthEast\t0\tHIGH\t1000\t1600\t1\t58699\t800\t0\nCU9346 \tDIVORCED\tCA \tM \tAuthor\tWest\t12746\tHIGH\t2100\t1600\t3\t61504\t800\t0\nCU399 \tMARRIED\tFL \tM \tAuthor\tSouth\t0\tVERY HIGH\t824\t1700\t1\t66895\t800\t1\nCU2199 \tMARRIED\tNY \tF \tAuthor\tNorthEast\t0\tVERY HIGH\t1300\t2000\t1\t66562\t1000\t0\nCU9640 \tMARRIED\tCA \tM \tAuthor\tWest\t362\tHIGH\t1410\t2000\t1\t58649\t700\t0\nCU1363 \tMARRIED\tCA \tF \tAuthor\tWest\t0\tHIGH\t1800\t2100\t1\t65757\t800\t0\nCU5713 \tDIVORCED\tNY \tF \tAuthor\tNorthEast\t99099\tVERY HIGH\t2000\t2200\t1\t64611\t900\t0\nCU10535 \tWIDOWED\tCA \tM \tAuthor\tWest\t649\tHIGH\t8200\t2200\t1\t60416\t800\t0\nCU5609 \tDIVORCED\tCA \tF \tAuthor\tWest\t0\tVERY HIGH\t2000\t2400\t1\t70739\t1600\t1\nCU2916 \tDIVORCED\tNY \tF \tAuthor\tNorthEast\t0\tHIGH\t2000\t2800\t1\t58276\t900\t0\nCU15838 \tDIVORCED\tMN \tF \tAuthor\tWest\t0\tHIGH\t3155\t2800\t1\t74584\t2500\t1\nCU5660 \tSINGLE\tCA \tM \tAuthor\tWest\t43941\tMEDIUM\t0\t3200\t0\t67706\t700\t0\nCU6142 \tDIVORCED\tMI \tF \tAuthor\tMidwest\t0\tHIGH\t1863\t3200\t1\t67374\t800\t0\nCU12436 \tDIVORCED\tNY \tF \tAuthor\tNorthEast\t8384\tHIGH\t4000\t3500\t1\t69671\t1000\t0\nCU7180 \tSINGLE\tNY \tM \tAuthor\tNorthEast\t0\tHIGH\t0\t4000\t0\t67010\t700\t0\nCU5649 \tWIDOWED\tCA \tF \tAuthor\tWest\t0\tHIGH\t5000\t4200\t1\t62906\t800\t0\nCU420 \tDIVORCED\tCA \tF \tAuthor\tWest\t1320\tHIGH\t3500\t4600\t1\t62422\t900\t0\nCU663 \tDIVORCED\tMI \tF \tAuthor\tMidwest\t0\tHIGH\t4213\t4700\t1\t62122\t3800\t0\nCU14091 \tMARRIED\tOR \tF \tAuthor\tWest\t0\tHIGH\t1500\t4900\t1\t58276\t1000\t1\nCU556 \tWIDOWED\tMI \tF \tAuthor\tMidwest\t0\tMEDIUM\t5000\t7000\t5\t65396\t800\t0\nCU14040 \tWIDOWED\tNY \tF \tAuthor\tNorthEast\t38196\tVERY HIGH\t10000\t7100\t1\t80511\t5000\t0\nCU5588 \tDIVORCED\tCA \tF \tAuthor\tWest\t0\tHIGH\t3500\t8200\t1\t62909\t500\t1\nCU5714 \tDIVORCED\tNY \tF \tAuthor\tNorthEast\t63670\tVERY HIGH\t4000\t8200\t5\t76058\t1600\t0\nCU6733 \tDIVORCED\tNY \tM \tAuthor\tNorthEast\t0\tHIGH\t3500\t8500\t1\t65630\t2000\t1\nCU232 \tWIDOWED\tCA \tF \tAuthor\tWest\t782\tMEDIUM\t5000\t9000\t6\t75938\t1600\t0\nCU1720 \tWIDOWED\tNY \tM \tAuthor\tNorthEast\t0\tHIGH\t5000\t9200\t1\t59255\t900\t0\nCU7073 \tDIVORCED\tUT \tF \tAuthor\tSouthwest\t77303\tHIGH\t2600\t9500\t1\t67870\t900\t0\nCU271 \tDIVORCED\tCA \tF \tAuthor\tWest\t0\tHIGH\t4368\t9700\t1\t58732\t800\t1\nCU6756 \tWIDOWED\tNY \tF \tAuthor\tNorthEast\t7042\tLOW\t0\t10000\t6\t80713\t3000\t0\nCU7314 \tWIDOWED\tMI \tF \tAuthor\tMidwest\t283935\tVERY HIGH\t6000\t20000\t1\t62083\t1100\t0\nCU13087 \tMARRIED\tMI \tM \tAuthor\tMidwest\t0\tHIGH\t1000\t201\t1\t62383\t1000\t0\nCU1468 \tSINGLE\tCA \tM \tAuthor\tWest\t47\tHIGH\t0\t250\t0\t60431\t600\t0\nCU1715 \tSINGLE\tCA \tM \tAuthor\tWest\t66091\tHIGH\t300\t250\t3\t59740\t800\t1\nCU1398 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tVERY HIGH\t700\t250\t1\t77596\t2500\t0\nCU1932 \tMARRIED\tCA \tF \tAuthor\tWest\t0\tMEDIUM\t1000\t250\t4\t62671\t700\t0\nCU5544 \tSINGLE\tMI \tM \tAuthor\tMidwest\t15355\tLOW\t530\t251\t1\t62121\t1000\t0\nCU7956 \tMARRIED\tNY \tF \tAuthor\tNorthEast\t0\tHIGH\t1500\t290\t2\t65328\t1000\t1\nCU12923 \tDIVORCED\tNY \tF \tAuthor\tNorthEast\t0\tHIGH\t2000\t351\t1\t68526\t1500\t1\nCU14034 \tMARRIED\tNY \tF \tAuthor\tNorthEast\t0\tHIGH\t746\t450\t1\t61929\t600\t0\nCU5535 \tMARRIED\tCA \tM \tAuthor\tWest\t67719\tVERY HIGH\t19285\t501\t1\t58849\t700\t0\nCU15423 \tMARRIED\tNY \tF \tAuthor\tNorthEast\t0\tHIGH\t1800\t510\t6\t60827\t1000\t1\nCU5001 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tHIGH\t1000\t701\t3\t66356\t1400\t0\nCU10151 \tMARRIED\tMI \tF \tAuthor\tMidwest\t0\tMEDIUM\t1500\t701\t5\t67365\t1000\t1\nCU6220 \tMARRIED\tCA \tF \tAuthor\tWest\t0\tHIGH\t1250\t750\t2\t56738\t1500\t0\nCU3453 \tDIVORCED\tCA \tF \tAuthor\tWest\t0\tHIGH\t3000\t901\t5\t65391\t1000\t0\nCU6224 \tDIVORCED\tNY \tM \tAuthor\tNorthEast\t0\tVERY HIGH\t3000\t901\t3\t57464\t1000\t0\nCU5758 \tSINGLE\tNC \tM \tAuthor\tSouth\t0\tHIGH\t356\t904\t3\t63917\t600\t1\nCU5525 \tMARRIED\tOH \tF \tAuthor\tMidwest\t42747\tVERY HIGH\t1700\t950\t1\t64091\t1000\t0\nCU1491 \tSINGLE\tCA \tM \tAuthor\tWest\t9398\tMEDIUM\t0\t1050\t0\t63935\t700\t0\nCU1546 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tHIGH\t1114\t1150\t3\t59500\t900\t0\nCU5589 \tMARRIED\tNC \tF \tAuthor\tSouth\t0\tMEDIUM\t1050\t1201\t6\t62786\t700\t0\nCU2617 \tDIVORCED\tLA \tM \tAuthor\tSouth\t0\tHIGH\t1903\t1201\t1\t62205\t1300\t0\nCU5260 \tMARRIED\tCA \tM \tAuthor\tWest\t0\tLOW\t1580\t1250\t6\t64032\t1200\t0\nCU8824 \tMARRIED\tNY \tF \tAuthor\tNorthEast\t0\tMEDIUM\t1100\t1350\t5\t67363\t800\t0\nCU5778 \tMARRIED\tNY \tM \tAuthor\tNorthEast\t0\tVERY HIGH\t1000\t1390\t1\t69723\t1500\t1\nCU1419 \tMARRIED\tMI \tF \tAuthor\tMidwest\t0\tMEDIUM\t1500\t1650\t6\t63850\t900\t0\nCU6006 \tMARRIED\tCA \tF \tAuthor\tWest\t2236\tVERY HIGH\t1500\t1650\t1\t59439\t800\t0\nCU6071 \tSINGLE\tMI \tM \tAuthor\tMidwest\t7129\tHIGH\t0\t1750\t0\t65628\t1800\t0\nCU5755 \tSINGLE\tMI \tM \tAuthor\tMidwest\t0\tVERY HIGH\t500\t1750\t0\t61342\t600\t0\nCU940 \tMARRIED\tCA \tF \tAuthor\tWest\t0\tHIGH\t1030\t1910\t1\t55916\t1400\t1\nCU5128 \tMARRIED\tMI \tF \tAuthor\tMidwest\t0\tHIGH\t1250\t1950\t1\t65562\t500\t0\nCU15924 \tDIVORCED\tUT \tF \tAuthor\tSouthwest\t0\tVERY HIGH\t2871\t1950\t1\t65821\t2500\t0\nCU6755 \tSINGLE\tMI \tM \tAuthor\tMidwest\t2071\tMEDIUM\t0\t2020\t0\t62846\t600\t0\nCU8870 \tDIVORCED\tNY \tF \tAuthor\tNorthEast\t239\tMEDIUM\t2602\t2450\t5\t64949\t800\t0\nCU6017 \tMARRIED\tMI \tF \tAuthor\tMidwest\t34524\tHIGH\t1500\t2526\t1\t57256\t1000\t0\nCU7475 \tMARRIED\tNY \tF \tAuthor\tNorthEast\t0\tVERY HIGH\t1500\t2550\t1\t70051\t1000\t0\nCU891 \tSINGLE\tOR \tM \tAuthor\tWest\t0\tHIGH\t0\t2640\t0\t59293\t1500\t0\nCU7263 \tDIVORCED\tNY \tF \tAuthor\tNorthEast\t0\tHIGH\t2500\t2750\t1\t62326\t1400\t0\nCU5998 \tMARRIED\tOR \tM \tAuthor\tWest\t0\tHIGH\t1524\t2903\t0\t63335\t900\t1\nCU6773 \tDIVORCED\tOK \tF \tAuthor\tMidwest\t0\tVERY HIGH\t2000\t3130\t1\t69025\t1000\t1\nCU15181 \tDIVORCED\tOR \tF \tAuthor\tWest\t0\tMEDIUM\t2000\t3150\t5\t71770\t1500\t1\nCU280 \tDIVORCED\tMI \tF \tAuthor\tMidwest\t0\tVERY HIGH\t2100\t3668\t1\t60478\t900\t0\nCU6215 \tDIVORCED\tNC \tF \tAuthor\tSouth\t0\tMEDIUM\t0\t3850\t1\t68155\t900\t1\nCU6526 \tDIVORCED\tOR \tM \tAuthor\tWest\t1076\tHIGH\t2323\t3950\t1\t72431\t1500\t0\nCU2630 \tDIVORCED\tNY \tF \tAuthor\tNorthEast\t0\tHIGH\t2500\t4050\t1\t69115\t800\t1\nCU5753 \tDIVORCED\tCA \tF \tAuthor\tWest\t0\tVERY HIGH\t2400\t4150\t1\t72706\t1400\t0\nCU880 \tMARRIED\tCA \tF \tAuthor\tWest\t12528\tHIGH\t1500\t4350\t1\t58899\t900\t1\nCU2080 \tSINGLE\tIL \tM \tAuthor\tMidwest\t0\tMEDIUM\t0\t4888\t0\t50045\t2500\t0\nCU656 \tSINGLE\tDC \tM \tAuthor\tNorthEast\t0\tLOW\t0\t5622\t0\t67545\t1300\t0\nCU6459 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tMEDIUM\t0\t7201\t1\t65801\t500\t0\nCU2616 \tDIVORCED\tMI \tF \tAuthor\tMidwest\t0\tVERY HIGH\t4000\t10100\t1\t78154\t2000\t0\nCU983 \tDIVORCED\tMI \tF \tAuthor\tMidwest\t0\tHIGH\t4000\t10200\t1\t63388\t500\t0\nCU665 \tWIDOWED\tMI \tF \tAuthor\tMidwest\t97906\tHIGH\t6600\t10600\t1\t65087\t1500\t0\nCU6752 \tWIDOWED\tMI \tF \tAuthor\tMidwest\t4315\tHIGH\t6300\t14100\t1\t62499\t800\t0\nCU5744 \tDIVORCED\tOR \tF \tAuthor\tWest\t0\tMEDIUM\t0\t15900\t1\t67971\t800\t0\nCU2797 \tWIDOWED\tCA \tF \tAuthor\tWest\t0\tHIGH\t6624\t16700\t1\t60046\t500\t0\nCU9970 \tWIDOWED\tUT \tF \tAuthor\tSouthwest\t0\tHIGH\t9000\t19100\t1\t73028\t4000\t0\nCU5678 \tWIDOWED\tCA \tF \tAuthor\tWest\t0\tLOW\t0\t19500\t6\t63766\t800\t0\nCU5554 \tWIDOWED\tMI \tF \tAuthor\tMidwest\t60477\tHIGH\t8000\t22000\t1\t71531\t1600\t0\nCU6471 \tWIDOWED\tNY \tF \tAuthor\tNorthEast\t162942\tVERY HIGH\t8700\t23100\t1\t80113\t4000\t0\nCU641 \tWIDOWED\tMI \tF \tAuthor\tMidwest\t0\tHIGH\t7000\t26500\t1\t71004\t3500\t0\nCU1660 \tDIVORCED\tMI \tF \tAuthor\tMidwest\t0\tHIGH\t4000\t10801\t3\t65649\t800\t0\nCU2856 \tSINGLE\tCA \tM \tAuthor\tWest\t0\tMEDIUM\t0\t11775\t0\t62233\t700\t0\nCU7577 \tWIDOWED\tCA \tM \tAuthor\tWest\t0\tVERY HIGH\t5000\t12835\t1\t68681\t800\t0\nCU3259 \tWIDOWED\tCA \tF \tAuthor\tWest\t25812\tMEDIUM\t5047\t12950\t6\t58183\t5000\t0\nCU10880 \tSINGLE\tNY \tM \tPROF-1\tNorthEast\t0\tMEDIUM\t0\t0\t0\t64418\t1000\t0\nCU12783 \tSINGLE\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t0\t0\t0\t67065\t700\t0\nCU14188 \tSINGLE\tCA \tM \tPROF-1\tWest\t0\tMEDIUM\t0\t0\t0\t59729\t2500\t0\nCU15232 \tSINGLE\tUT \tM \tPROF-1\tSouthwest\t0\tMEDIUM\t0\t0\t4\t74389\t2500\t0\nCU5042 \tSINGLE\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t0\t0\t0\t70961\t900\t0\nCU7396 \tSINGLE\tMI \tM \tPROF-1\tMidwest\t0\tMEDIUM\t0\t0\t0\t59092\t700\t0\nCU8478 \tSINGLE\tCA \tM \tPROF-1\tWest\t0\tMEDIUM\t0\t0\t0\t64627\t700\t0\nCU14727 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t700\t0\t1\t62090\t600\t0\nCU1727 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t1000\t0\t1\t61838\t900\t0\nCU10358 \tMARRIED\tCA \tM \tPROF-1\tWest\t0\tMEDIUM\t1200\t0\t3\t67498\t1500\t0\nCU11310 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tVERY HIGH\t1200\t0\t1\t80704\t2500\t0\nCU14316 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t1200\t0\t4\t86071\t2500\t0\nCU9339 \tMARRIED\tNV \tM \tPROF-1\tSouthwest\t0\tMEDIUM\t1200\t0\t1\t55423\t1500\t0\nCU13410 \tMARRIED\tWA \tM \tPROF-1\tWest\t0\tVERY HIGH\t1500\t0\t1\t72168\t1500\t0\nCU15122 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tMEDIUM\t1500\t0\t4\t66122\t1500\t0\nCU11152 \tMARRIED\tCA \tF \tPROF-1\tWest\t0\tHIGH\t1600\t0\t1\t65110\t1000\t0\nCU10453 \tDIVORCED\tCA \tF \tPROF-1\tWest\t0\tHIGH\t2000\t0\t1\t76390\t1500\t0\nCU6857 \tDIVORCED\tMI \tF \tPROF-1\tMidwest\t0\tHIGH\t2500\t0\t1\t70412\t1500\t0\nCU8207 \tDIVORCED\tNY \tF \tPROF-1\tNorthEast\t0\tHIGH\t3500\t0\t1\t65316\t2000\t0\nCU13555 \tDIVORCED\tCA \tM \tPROF-1\tWest\t0\tHIGH\t4000\t0\t1\t61478\t2000\t0\nCU2182 \tDIVORCED\tCA \tM \tPROF-1\tWest\t0\tMEDIUM\t4800\t0\t5\t65553\t500\t0\nCU14066 \tSINGLE\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t250\t0\t3\t62817\t600\t0\nCU15857 \tSINGLE\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t437\t0\t1\t61993\t1500\t0\nCU10989 \tSINGLE\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t633\t0\t1\t65007\t600\t0\nCU8453 \tSINGLE\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t650\t0\t2\t56889\t2500\t0\nCU14671 \tSINGLE\tMN \tM \tPROF-1\tWest\t0\tHIGH\t662\t0\t2\t71157\t2500\t0\nCU12546 \tMARRIED\tMI \tM \tPROF-1\tMidwest\t0\tHIGH\t1098\t0\t1\t62034\t700\t0\nCU13554 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t1205\t0\t1\t73123\t1500\t0\nCU2562 \tDIVORCED\tMI \tM \tPROF-1\tMidwest\t0\tHIGH\t2910\t0\t0\t61384\t500\t0\nCU13524 \tMARRIED\tCA \tM \tPROF-1\tWest\t0\tHIGH\t1000\t500\t3\t62447\t1000\t1\nCU14932 \tMARRIED\tMI \tM \tPROF-1\tMidwest\t0\tHIGH\t1000\t500\t3\t61563\t700\t0\nCU13956 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t1400\t500\t1\t74323\t1500\t0\nCU11206 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t1500\t500\t1\t68925\t1500\t0\nCU7795 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tMEDIUM\t1500\t500\t3\t58598\t1500\t0\nCU7808 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t1000\t600\t3\t71331\t1000\t0\nCU10912 \tSINGLE\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t600\t700\t1\t62623\t700\t0\nCU13336 \tDIVORCED\tMI \tF \tPROF-1\tMidwest\t0\tHIGH\t2101\t700\t1\t65065\t1500\t1\nCU12744 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t1000\t800\t3\t69954\t1000\t0\nCU13110 \tDIVORCED\tNY \tM \tPROF-1\tNorthEast\t0\tVERY HIGH\t2000\t900\t1\t76802\t1500\t0\nCU8243 \tDIVORCED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t3000\t900\t1\t61162\t1500\t0\nCU15962 \tDIVORCED\tUT \tM \tPROF-1\tSouthwest\t0\tVERY HIGH\t2500\t1400\t3\t79409\t2500\t1\nCU12738 \tDIVORCED\tNY \tF \tPROF-1\tNorthEast\t0\tHIGH\t2200\t1500\t1\t60526\t1500\t1\nCU9417 \tMARRIED\tCA \tF \tPROF-1\tWest\t0\tHIGH\t1010\t1600\t1\t62958\t700\t0\nCU7124 \tDIVORCED\tNY \tF \tPROF-1\tNorthEast\t0\tHIGH\t2000\t2000\t1\t60742\t900\t1\nCU11688 \tDIVORCED\tWI \tF \tPROF-1\tMidwest\t0\tMEDIUM\t2215\t2100\t5\t58593\t2500\t1\nCU6592 \tDIVORCED\tNC \tM \tPROF-1\tSouth\t0\tMEDIUM\t2000\t2300\t3\t65992\t900\t0\nCU5430 \tDIVORCED\tMI \tF \tPROF-1\tMidwest\t0\tVERY HIGH\t4000\t3900\t1\t62937\t1000\t1\nCU12049 \tMARRIED\tCA \tM \tPROF-1\tWest\t0\tHIGH\t10000\t8000\t2\t75628\t5000\t1\nCU15660 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tVERY HIGH\t823\t450\t1\t64403\t600\t0\nCU7825 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t1001\t880\t3\t56250\t2500\t1\nCU2899 \tMARRIED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t896\t935\t3\t68522\t900\t0\nCU15137 \tDIVORCED\tIL \tM \tPROF-1\tMidwest\t0\tHIGH\t2000\t950\t1\t63670\t1500\t1\nCU15846 \tDIVORCED\tNY \tM \tPROF-1\tNorthEast\t0\tHIGH\t2000\t950\t1\t53294\t2500\t0\nCU7572 \tDIVORCED\tNY \tF \tPROF-1\tNorthEast\t0\tVERY HIGH\t2500\t2950\t1\t76274\t1500\t0\nCU9846 \tDIVORCED\tNY \tF \tPROF-1\tNorthEast\t0\tHIGH\t3000\t3290\t1\t70125\t1500\t0\nCU14218 \tDIVORCED\tNY \tF \tPROF-1\tNorthEast\t0\tMEDIUM\t4900\t3850\t5\t54307\t3000\t1\nCU4207 \tSINGLE\tMI \tM \tPROF-1\tMidwest\t0\tMEDIUM\t0\t4085\t1\t66700\t800\t0\nCU3065 \tDIVORCED\tNY \tF \tPROF-1\tNorthEast\t0\tHIGH\t2300\t6282\t1\t66372\t1300\t0\nCU9486 \tDIVORCED\tCA \tF \tPROF-1\tWest\t0\tHIGH\t4000\t12000\t1\t57888\t1000\t0\nCU10369 \tSINGLE\tFL \tM \tPROF-2\tSouth\t0\tHIGH\t0\t0\t0\t70711\t1500\t0\nCU13045 \tSINGLE\tOR \tM \tPROF-2\tWest\t0\tLOW\t0\t0\t4\t62378\t600\t0\nCU13388 \tSINGLE\tMI \tM \tPROF-2\tMidwest\t0\tMEDIUM\t0\t0\t2\t54484\t2500\t0\nCU1381 \tSINGLE\tCA \tM \tPROF-2\tWest\t0\tLOW\t0\t0\t0\t66774\t1500\t0\nCU1421 \tSINGLE\tCA \tM \tPROF-2\tWest\t0\tHIGH\t0\t0\t0\t57809\t1400\t0\nCU15810 \tSINGLE\tWI \tM \tPROF-2\tMidwest\t0\tLOW\t0\t0\t6\t67348\t2500\t0\nCU5226 \tSINGLE\tCA \tM \tPROF-2\tWest\t0\tMEDIUM\t0\t0\t0\t62780\t900\t0\nCU5385 \tSINGLE\tCA \tM \tPROF-2\tWest\t0\tMEDIUM\t0\t0\t0\t65839\t500\t0\nCU5829 \tSINGLE\tMI \tM \tPROF-2\tMidwest\t0\tLOW\t0\t0\t0\t66157\t900\t0\nCU6408 \tSINGLE\tMI \tM \tPROF-2\tMidwest\t0\tMEDIUM\t0\t0\t3\t61425\t600\t0\nCU9767 \tSINGLE\tWA \tM \tPROF-2\tWest\t0\tMEDIUM\t0\t0\t1\t69603\t800\t0\nCU6754 \tSINGLE\tCA \tM \tPROF-2\tWest\t0\tHIGH\t600\t0\t4\t67940\t600\t0\nCU9988 \tSINGLE\tMI \tM \tPROF-2\tMidwest\t0\tMEDIUM\t600\t0\t3\t64887\t1000\t0\nCU6332 \tMARRIED\tCA \tM \tPROF-2\tWest\t0\tVERY HIGH\t700\t0\t6\t62898\t600\t0\nCU10820 \tMARRIED\tCA \tF \tPROF-2\tWest\t0\tHIGH\t1100\t0\t6\t66878\t800\t0\nCU8356 \tMARRIED\tMO \tM \tPROF-2\tMidwest\t0\tHIGH\t1100\t0\t2\t70765\t1000\t0\nCU9917 \tMARRIED\tDC \tM \tPROF-2\tNorthEast\t0\tMEDIUM\t1700\t0\t6\t64880\t1000\t0\nCU14283 \tDIVORCED\tMI \tF \tPROF-2\tMidwest\t0\tMEDIUM\t3000\t0\t5\t57814\t2500\t0\nCU12004 \tWIDOWED\tDC \tF \tPROF-2\tNorthEast\t0\tVERY HIGH\t5800\t0\t4\t96956\t5000\t0\nCU11881 \tSINGLE\tOR \tM \tPROF-2\tWest\t0\tMEDIUM\t545\t0\t6\t59152\t700\t0\nCU6400 \tMARRIED\tMI \tM \tPROF-2\tMidwest\t0\tMEDIUM\t670\t0\t6\t62563\t1200\t0\nCU466 \tMARRIED\tCA \tM \tPROF-2\tWest\t0\tLOW\t1002\t0\t6\t64768\t500\t0\nCU15036 \tMARRIED\tNY \tF \tPROF-2\tNorthEast\t3704\tMEDIUM\t1020\t0\t6\t61352\t700\t0\nCU10977 \tMARRIED\tOR \tF \tPROF-2\tWest\t89\tVERY HIGH\t1381\t0\t1\t62260\t1500\t0\nCU6981 \tMARRIED\tOH \tM \tPROF-2\tMidwest\t0\tHIGH\t1627\t0\t0\t67481\t900\t0\nCU13261 \tDIVORCED\tCA \tF \tPROF-2\tWest\t0\tVERY HIGH\t2832\t0\t1\t65936\t1000\t0\nCU14043 \tMARRIED\tNM \tM \tPROF-2\tSouthwest\t0\tHIGH\t10879\t0\t1\t58097\t5000\t0\nCU9760 \tSINGLE\tCO \tF \tPROF-2\tWest\t0\tHIGH\t448\t500\t3\t60882\t700\t0\nCU12974 \tMARRIED\tNY \tF \tPROF-2\tNorthEast\t0\tMEDIUM\t830\t500\t6\t68540\t2500\t0\nCU9879 \tMARRIED\tNY \tM \tPROF-2\tNorthEast\t0\tHIGH\t1500\t600\t6\t59872\t800\t0\nCU12737 \tSINGLE\tMS \tM \tPROF-2\tSouth\t0\tHIGH\t600\t800\t1\t65146\t1000\t1\nCU11474 \tMARRIED\tMI \tF \tPROF-2\tMidwest\t0\tMEDIUM\t1720\t1300\t6\t64290\t1500\t1\nCU13277 \tSINGLE\tCA \tM \tPROF-2\tWest\t0\tLOW\t0\t1500\t3\t70972\t1000\t0\nCU10921 \tDIVORCED\tCA \tF \tPROF-2\tWest\t0\tHIGH\t3235\t2100\t3\t63000\t1000\t1\nCU6501 \tDIVORCED\tCA \tF \tPROF-2\tWest\t4856\tMEDIUM\t2000\t2300\t6\t70907\t1000\t0\nCU12997 \tDIVORCED\tMS \tF \tPROF-2\tSouth\t0\tHIGH\t4000\t3600\t6\t85119\t4000\t1\nCU12176 \tWIDOWED\tCA \tF \tPROF-2\tWest\t0\tMEDIUM\t8635\t6500\t6\t66822\t5000\t1\nCU15989 \tMARRIED\tUT \tF \tPROF-2\tSouthwest\t0\tHIGH\t764\t250\t3\t55056\t2500\t0\nCU10861 \tMARRIED\tCA \tF \tPROF-2\tWest\t0\tMEDIUM\t1500\t591\t6\t69237\t1000\t1\nCU12673 \tMARRIED\tCA \tM \tPROF-2\tWest\t0\tHIGH\t1070\t650\t3\t68522\t1000\t1\nCU9899 \tMARRIED\tCA \tM \tPROF-2\tWest\t0\tMEDIUM\t850\t1450\t3\t62296\t700\t1\nCU12623 \tDIVORCED\tCA \tF \tPROF-2\tWest\t0\tMEDIUM\t2100\t1650\t6\t65388\t1500\t1\nCU1482 \tDIVORCED\tCA \tM \tPROF-2\tWest\t0\tMEDIUM\t2300\t1801\t6\t58697\t900\t0\nCU4315 \tDIVORCED\tOR \tF \tPROF-2\tWest\t0\tMEDIUM\t1940\t2330\t3\t61790\t500\t1\nCU6718 \tMARRIED\tCA \tF \tPROF-2\tWest\t0\tMEDIUM\t1200\t2350\t6\t59755\t700\t0\nCU14376 \tDIVORCED\tNY \tM \tPROF-2\tNorthEast\t0\tHIGH\t3420\t2950\t3\t66196\t2000\t0\nCU12337 \tSINGLE\tMS \tM \tPROF-3\tSouth\t0\tMEDIUM\t0\t0\t3\t76895\t1500\t0\nCU14332 \tSINGLE\tDC \tM \tPROF-3\tNorthEast\t0\tMEDIUM\t0\t0\t3\t67794\t1500\t0\nCU15896 \tSINGLE\tUT \tM \tPROF-3\tSouthwest\t0\tMEDIUM\t0\t0\t3\t75121\t1500\t0\nCU5135 \tSINGLE\tCA \tM \tPROF-3\tWest\t0\tLOW\t0\t0\t3\t62508\t500\t0\nCU5157 \tSINGLE\tCA \tM \tPROF-3\tWest\t0\tHIGH\t0\t0\t0\t69691\t1500\t0\nCU7998 \tSINGLE\tNY \tF \tPROF-3\tNorthEast\t0\tLOW\t0\t0\t5\t58601\t700\t0\nCU9623 \tSINGLE\tNY \tM \tPROF-3\tNorthEast\t0\tLOW\t0\t0\t3\t72870\t1500\t0\nCU15849 \tSINGLE\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t200\t0\t3\t61764\t2500\t0\nCU15908 \tSINGLE\tUT \tM \tPROF-3\tSouthwest\t0\tHIGH\t300\t0\t3\t63487\t1500\t0\nCU8312 \tSINGLE\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t300\t0\t3\t62985\t1000\t0\nCU14662 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t101\tHIGH\t700\t0\t3\t64180\t2500\t0\nCU11314 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t800\t0\t3\t59487\t1500\t0\nCU12604 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tMEDIUM\t1000\t0\t3\t70752\t1000\t0\nCU10466 \tMARRIED\tCA \tM \tPROF-3\tWest\t0\tHIGH\t1300\t0\t3\t61594\t1500\t0\nCU15569 \tMARRIED\tNY \tF \tPROF-3\tNorthEast\t0\tVERY HIGH\t1800\t0\t1\t71084\t1500\t0\nCU1891 \tDIVORCED\tNY \tM \tPROF-3\tNorthEast\t0\tVERY HIGH\t2000\t0\t0\t68002\t1500\t0\nCU1423 \tDIVORCED\tNY \tM \tPROF-3\tNorthEast\t0\tMEDIUM\t2100\t0\t1\t59495\t1000\t0\nCU15292 \tSINGLE\tUT \tF \tPROF-3\tSouthwest\t0\tMEDIUM\t117\t0\t5\t66654\t2500\t0\nCU7639 \tSINGLE\tMI \tM \tPROF-3\tMidwest\t0\tHIGH\t218\t0\t3\t57203\t1500\t0\nCU15961 \tSINGLE\tUT \tM \tPROF-3\tSouthwest\t0\tHIGH\t225\t0\t3\t70977\t1500\t0\nCU11335 \tSINGLE\tMI \tM \tPROF-3\tMidwest\t0\tHIGH\t250\t0\t1\t65824\t600\t0\nCU12216 \tSINGLE\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t350\t0\t3\t59108\t600\t0\nCU6159 \tSINGLE\tNY \tM \tPROF-3\tNorthEast\t0\tVERY HIGH\t380\t0\t0\t70437\t1000\t0\nCU6087 \tSINGLE\tCA \tM \tPROF-3\tWest\t0\tVERY HIGH\t550\t0\t1\t62702\t2500\t0\nCU1640 \tMARRIED\tNY \tF \tPROF-3\tNorthEast\t0\tMEDIUM\t817\t0\t5\t60337\t500\t0\nCU13743 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t1180\t0\t1\t67213\t1000\t0\nCU9106 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tVERY HIGH\t1540\t0\t1\t69883\t800\t0\nCU13141 \tDIVORCED\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t2000\t300\t3\t72112\t1500\t0\nCU11916 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tLOW\t700\t500\t3\t63104\t1000\t1\nCU12476 \tMARRIED\tCA \tM \tPROF-3\tWest\t0\tMEDIUM\t800\t500\t3\t60311\t600\t1\nCU15835 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t700\t600\t3\t66553\t1500\t1\nCU14143 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t1300\t800\t1\t62781\t700\t0\nCU15580 \tDIVORCED\tMI \tF \tPROF-3\tMidwest\t0\tMEDIUM\t2000\t1100\t5\t63454\t1500\t0\nCU12238 \tMARRIED\tNY \tF \tPROF-3\tNorthEast\t0\tHIGH\t1500\t1200\t5\t76322\t1500\t1\nCU8076 \tDIVORCED\tNY \tM \tPROF-3\tNorthEast\t0\tMEDIUM\t4000\t1600\t5\t62171\t2000\t1\nCU15436 \tDIVORCED\tNY \tF \tPROF-3\tNorthEast\t0\tMEDIUM\t2500\t2300\t6\t57669\t1500\t1\nCU3073 \tMARRIED\tMI \tM \tPROF-3\tMidwest\t0\tHIGH\t1700\t3500\t1\t63255\t1400\t1\nCU8894 \tDIVORCED\tNY \tM \tPROF-3\tNorthEast\t0\tMEDIUM\t3500\t4200\t3\t66809\t1000\t1\nCU15573 \tMARRIED\tMN \tM \tPROF-3\tWest\t0\tHIGH\t5500\t4800\t1\t88921\t5000\t1\nCU4419 \tDIVORCED\tCA \tF \tPROF-3\tWest\t0\tVERY HIGH\t3126\t6200\t1\t62186\t1200\t1\nCU10655 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tMEDIUM\t700\t250\t3\t67863\t1000\t0\nCU10736 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tMEDIUM\t1000\t250\t3\t66573\t1000\t0\nCU13001 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t700\t290\t3\t64440\t1500\t1\nCU14276 \tMARRIED\tDC \tM \tPROF-3\tNorthEast\t0\tMEDIUM\t1000\t450\t3\t68801\t1000\t1\nCU14055 \tDIVORCED\tNY \tF \tPROF-3\tNorthEast\t0\tMEDIUM\t1900\t551\t5\t62619\t1500\t0\nCU15713 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t770\t650\t3\t68897\t1000\t1\nCU10965 \tMARRIED\tNY \tM \tPROF-3\tNorthEast\t0\tMEDIUM\t1200\t850\t3\t67365\t1500\t0\nCU10867 \tMARRIED\tNY \tF \tPROF-3\tNorthEast\t0\tHIGH\t949\t850\t1\t71214\t1000\t1\nCU12641 \tMARRIED\tMS \tM \tPROF-3\tSouth\t0\tHIGH\t1369\t1050\t3\t55367\t1500\t0\nCU11002 \tDIVORCED\tNY \tM \tPROF-3\tNorthEast\t0\tHIGH\t2468\t1950\t3\t73402\t1500\t0\nCU12698 \tDIVORCED\tNY \tM \tPROF-3\tNorthEast\t0\tMEDIUM\t2850\t2550\t3\t61610\t1500\t1\nCU6683 \tDIVORCED\tNY \tM \tPROF-3\tNorthEast\t0\tVERY HIGH\t3000\t4001\t0\t69003\t800\t0\nCU1884 \tWIDOWED\tNY \tF \tPROF-3\tNorthEast\t0\tVERY HIGH\t5000\t11400\t1\t65908\t500\t0\nCU6307 \tMARRIED\tMI \tF \tPROF-3\tMidwest\t0\tVERY HIGH\t5000\t14100\t1\t60024\t1000\t1\nCU12503 \tSINGLE\tCA \tM \tPROF-4\tWest\t0\tMEDIUM\t0\t0\t0\t58658\t1000\t0\nCU14065 \tSINGLE\tCA \tM \tPROF-4\tWest\t0\tMEDIUM\t0\t0\t3\t66455\t1000\t0\nCU14359 \tSINGLE\tCA \tM \tPROF-4\tWest\t0\tMEDIUM\t0\t0\t2\t67364\t600\t0\nCU4540 \tSINGLE\tMI \tM \tPROF-4\tMidwest\t0\tHIGH\t0\t0\t0\t66480\t700\t0\nCU4873 \tSINGLE\tMS \tM \tPROF-4\tSouth\t0\tHIGH\t0\t0\t0\t63718\t900\t0\nCU7624 \tSINGLE\tMS \tM \tPROF-4\tSouth\t0\tHIGH\t0\t0\t0\t65601\t800\t0\nCU7625 \tSINGLE\tMS \tM \tPROF-4\tSouth\t0\tHIGH\t0\t0\t0\t76799\t1500\t0\nCU7836 \tSINGLE\tAL \tM \tPROF-4\tSouth\t0\tMEDIUM\t0\t0\t0\t55971\t1500\t0\nCU13702 \tSINGLE\tCA \tM \tPROF-4\tWest\t0\tHIGH\t500\t0\t3\t63247\t600\t0\nCU13069 \tMARRIED\tCO \tF \tPROF-4\tWest\t0\tHIGH\t1000\t0\t1\t71810\t1000\t0\nCU11069 \tMARRIED\tCA \tF \tPROF-4\tWest\t0\tHIGH\t10000\t0\t2\t58083\t800\t0\nCU11931 \tSINGLE\tMI \tM \tPROF-4\tMidwest\t0\tHIGH\t188\t0\t3\t67790\t700\t0\nCU8430 \tSINGLE\tCA \tM \tPROF-4\tWest\t0\tHIGH\t371\t0\t3\t73997\t2500\t0\nCU14068 \tSINGLE\tCA \tM \tPROF-4\tWest\t0\tHIGH\t396\t0\t3\t70937\t1000\t0\nCU1471 \tSINGLE\tAL \tM \tPROF-4\tSouth\t0\tHIGH\t502\t0\t3\t66361\t500\t0\nCU12236 \tSINGLE\tCA \tM \tPROF-4\tWest\t0\tHIGH\t530\t0\t4\t61200\t600\t0\nCU11745 \tSINGLE\tCA \tM \tPROF-4\tWest\t0\tMEDIUM\t624\t0\t3\t59012\t1000\t0\nCU8996 \tMARRIED\tCA \tF \tPROF-4\tWest\t0\tHIGH\t722\t0\t1\t59400\t700\t0\nCU15710 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tHIGH\t727\t0\t3\t66030\t600\t0\nCU12821 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tHIGH\t827\t0\t3\t65758\t700\t0\nCU8111 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tHIGH\t1367\t0\t3\t65679\t1500\t0\nCU7868 \tMARRIED\tMI \tM \tPROF-4\tMidwest\t0\tHIGH\t1600\t400\t3\t73743\t1500\t0\nCU4872 \tMARRIED\tMI \tM \tPROF-4\tMidwest\t0\tMEDIUM\t814\t500\t3\t64611\t500\t0\nCU7556 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tMEDIUM\t700\t600\t4\t65278\t600\t0\nCU6621 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tHIGH\t1231\t600\t4\t67378\t900\t0\nCU1483 \tMARRIED\tMI \tM \tPROF-4\tMidwest\t0\tHIGH\t1000\t800\t2\t58003\t800\t0\nCU10738 \tMARRIED\tMO \tF \tPROF-4\tMidwest\t0\tHIGH\t1800\t900\t1\t68035\t1500\t1\nCU7398 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tMEDIUM\t1000\t1100\t3\t59631\t700\t1\nCU12132 \tDIVORCED\tCA \tM \tPROF-4\tWest\t0\tMEDIUM\t2120\t1200\t3\t62019\t1500\t1\nCU6542 \tMARRIED\tMI \tM \tPROF-4\tMidwest\t0\tMEDIUM\t1438\t1400\t3\t62531\t900\t1\nCU14459 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tVERY HIGH\t1672\t1400\t3\t66686\t1000\t0\nCU9084 \tMARRIED\tCA \tF \tPROF-4\tWest\t0\tMEDIUM\t1401\t1600\t4\t69352\t800\t1\nCU175 \tDIVORCED\tCA \tM \tPROF-4\tWest\t0\tVERY HIGH\t2110\t2500\t3\t68330\t900\t0\nCU10039 \tDIVORCED\tMI \tM \tPROF-4\tMidwest\t0\tHIGH\t2800\t2700\t1\t73212\t1500\t1\nCU6730 \tDIVORCED\tCA \tM \tPROF-4\tWest\t24762\tHIGH\t3000\t3400\t2\t69820\t1000\t0\nCU14477 \tDIVORCED\tCO \tF \tPROF-4\tWest\t0\tHIGH\t4000\t5600\t1\t60671\t2000\t1\nCU13476 \tMARRIED\tMI \tM \tPROF-4\tMidwest\t0\tHIGH\t700\t251\t3\t63692\t1000\t0\nCU8708 \tMARRIED\tAL \tF \tPROF-4\tSouth\t0\tMEDIUM\t976\t251\t5\t63588\t1000\t0\nCU8846 \tSINGLE\tMI \tM \tPROF-4\tMidwest\t44\tMEDIUM\t635\t350\t3\t66663\t1500\t0\nCU13935 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tHIGH\t870\t450\t1\t67855\t600\t1\nCU2341 \tSINGLE\tCA \tM \tPROF-4\tWest\t0\tMEDIUM\t0\t650\t3\t67949\t600\t0\nCU12207 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tHIGH\t800\t650\t3\t65722\t1000\t0\nCU12727 \tMARRIED\tCA \tF \tPROF-4\tWest\t0\tHIGH\t750\t650\t1\t64328\t600\t1\nCU15166 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tMEDIUM\t1000\t750\t3\t68001\t700\t1\nCU10354 \tMARRIED\tCA \tM \tPROF-4\tWest\t0\tMEDIUM\t780\t850\t4\t60606\t800\t0\nCU15062 \tDIVORCED\tNY \tM \tPROF-4\tNorthEast\t0\tHIGH\t2200\t1050\t1\t62018\t1000\t1\nCU3436 \tDIVORCED\tMI \tM \tPROF-4\tMidwest\t0\tHIGH\t1819\t1550\t3\t71533\t1000\t1\nCU12937 \tMARRIED\tCA \tF \tPROF-4\tWest\t0\tHIGH\t1600\t1850\t1\t62402\t1500\t1\nCU4432 \tDIVORCED\tMI \tM \tPROF-4\tMidwest\t3104\tMEDIUM\t2574\t2750\t3\t66342\t500\t0\nCU13038 \tDIVORCED\tOK \tF \tPROF-4\tMidwest\t0\tHIGH\t4500\t3350\t1\t67615\t3000\t1\nCU6297 \tDIVORCED\tNY \tF \tPROF-4\tNorthEast\t0\tHIGH\t3000\t4150\t1\t72554\t1500\t1\nCU6022 \tSINGLE\tNY \tM \tPROF-4\tNorthEast\t115689\tMEDIUM\t0\t4733\t0\t74213\t1400\t0\nCU8609 \tDIVORCED\tCA \tF \tPROF-4\tWest\t0\tMEDIUM\t3317\t5970\t5\t61495\t800\t1\nCU9386 \tMARRIED\tCA \tF \tPROF-4\tWest\t0\tMEDIUM\t10000\t14100\t3\t65622\t1500\t1\nCU647 \tDIVORCED\tCA \tM \tPROF-4\tWest\t0\tVERY HIGH\t2000\t11230\t1\t65622\t1000\t0\nCU5211 \tSINGLE\tCA \tM \tPROF-4\tWest\t54473\tMEDIUM\t0\t14858\t0\t62733\t500\t0\nCU11680 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tMEDIUM\t0\t0\t0\t54836\t1500\t0\nCU12507 \tSINGLE\tOR \tM \tPROF-5\tWest\t0\tMEDIUM\t0\t0\t3\t63690\t600\t0\nCU12998 \tSINGLE\tCA \tM \tPROF-5\tWest\t0\tMEDIUM\t0\t0\t1\t52359\t2500\t0\nCU1371 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tMEDIUM\t0\t0\t3\t61758\t1000\t0\nCU14318 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tMEDIUM\t0\t0\t0\t64283\t1500\t0\nCU14320 \tSINGLE\tCA \tM \tPROF-5\tWest\t0\tHIGH\t0\t0\t3\t85737\t2500\t0\nCU15231 \tSINGLE\tUT \tM \tPROF-5\tSouthwest\t0\tLOW\t0\t0\t3\t64993\t900\t0\nCU15742 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tHIGH\t0\t0\t0\t84768\t2500\t0\nCU15753 \tSINGLE\tNV \tM \tPROF-5\tSouthwest\t0\tMEDIUM\t0\t0\t1\t66239\t2500\t0\nCU15862 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tMEDIUM\t0\t0\t1\t78402\t2500\t0\nCU15880 \tSINGLE\tUT \tM \tPROF-5\tSouthwest\t0\tLOW\t0\t0\t3\t54924\t2500\t0\nCU15918 \tSINGLE\tUT \tM \tPROF-5\tSouthwest\t0\tMEDIUM\t0\t0\t3\t69080\t1500\t0\nCU2559 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tHIGH\t0\t0\t0\t69597\t900\t0\nCU7819 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tLOW\t0\t0\t3\t60238\t1000\t0\nCU7829 \tSINGLE\tCA \tM \tPROF-5\tWest\t0\tMEDIUM\t0\t0\t0\t64954\t1500\t0\nCU8842 \tSINGLE\tFL \tM \tPROF-5\tSouth\t0\tMEDIUM\t0\t0\t0\t66875\t800\t0\nCU8844 \tSINGLE\tWI \tM \tPROF-5\tMidwest\t0\tMEDIUM\t0\t0\t0\t71263\t1500\t0\nCU8887 \tSINGLE\tFL \tM \tPROF-5\tSouth\t0\tHIGH\t0\t0\t0\t73257\t1500\t0\nCU8915 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tMEDIUM\t0\t0\t0\t70401\t1000\t0\nCU9624 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tHIGH\t0\t0\t0\t71760\t1500\t0\nCU15471 \tSINGLE\tCA \tM \tPROF-5\tWest\t0\tHIGH\t400\t0\t1\t62911\t600\t0\nCU14017 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tHIGH\t500\t0\t3\t67515\t600\t0\nCU14868 \tMARRIED\tNY \tM \tPROF-5\tNorthEast\t0\tMEDIUM\t700\t0\t3\t57297\t1000\t0\nCU2625 \tMARRIED\tNY \tM \tPROF-5\tNorthEast\t3262\tHIGH\t700\t0\t2\t62599\t500\t0\nCU7653 \tMARRIED\tNY \tM \tPROF-5\tNorthEast\t0\tHIGH\t700\t0\t3\t58239\t1500\t0\nCU12234 \tMARRIED\tNY \tM \tPROF-5\tNorthEast\t411\tHIGH\t1000\t0\t4\t69542\t1000\t0\nCU13145 \tMARRIED\tNY \tM \tPROF-5\tNorthEast\t0\tHIGH\t1000\t0\t3\t62613\t1000\t0\nCU15937 \tMARRIED\tUT \tM \tPROF-5\tSouthwest\t0\tMEDIUM\t1000\t0\t3\t55483\t1500\t0\nCU8319 \tMARRIED\tNY \tM \tPROF-5\tNorthEast\t0\tHIGH\t1000\t0\t3\t68276\t1000\t0\nCU9646 \tMARRIED\tNY \tM \tPROF-5\tNorthEast\t0\tHIGH\t1000\t0\t1\t68138\t700\t0\nCU11301 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tLOW\t150\t0\t3\t64340\t1500\t0\nCU14876 \tSINGLE\tCA \tM \tPROF-5\tWest\t0\tHIGH\t164\t0\t1\t59840\t600\t0\nCU9299 \tSINGLE\tNV \tM \tPROF-5\tSouthwest\t0\tHIGH\t210\t0\t3\t57581\t1500\t0\nCU14968 \tSINGLE\tNV \tM \tPROF-5\tSouthwest\t0\tHIGH\t239\t0\t4\t70281\t1000\t0\nCU11741 \tSINGLE\tNY \tM \tPROF-5\tNorthEast\t0\tHIGH\t250\t0\t1\t64235\t1000\t0\nCU9102 \tSINGLE\tCA \tM \tPROF-5\tWest\t0\tHIGH\t288\t0\t3\t65843\t700\t0\nCU2626 \tMARRIED\tMN \tM \tPROF-5\tWest\t0\tHIGH\t778\t0\t1\t60473\t900\t0\nCU10503 \tDIVORCED\tCA \tM \tPROF-5\tWest\t0\tHIGH\t2508\t0\t1\t71002\t1500\t0\nCU11686 \tDIVORCED\tCA \tF \tPROF-5\tWest\t0\tHIGH\t3875\t0\t5\t78546\t2500\t0\nCU7667 \tMARRIED\tCO \tM \tPROF-5\tWest\t0\tHIGH\t800\t200\t3\t60654\t1500\t0\nCU11256 \tMARRIED\tCA \tM \tPROF-5\tWest\t0\tHIGH\t701\t600\t1\t64220\t600\t1\nCU11750 \tMARRIED\tNY \tM \tPROF-5\tNorthEast\t0\tHIGH\t1050\t600\t3\t63827\t1000\t0\nCU9839 \tMARRIED\tCA \tM \tPROF-5\tWest\t0\tMEDIUM\t700\t900\t6\t66180\t800\t0\nCU7389 \tSINGLE\tCA \tM \tPROF-5\tWest\t0\tMEDIUM\t0\t1200\t0\t61908\t800\t1\nCU15645 \tMARRIED\tCA \tM \tPROF-5\tWest\t0\tMEDIUM\t1700\t1300\t3\t71881\t1500\t0\nCU12970 \tMARRIED\tCO \tM \tPROF-5\tWest\t0\tHIGH\t800\t650\t3\t58589\t2500\t1\nCU8839 \tMARRIED\tCA \tM \tPROF-5\tWest\t0\tVERY HIGH\t1289\t1250\t1\t63058\t1500\t0\nCU6590 \tMARRIED\tNY \tM \tPROF-5\tNorthEast\t64120\tVERY HIGH\t1380\t2396\t3\t69348\t1500\t0\nCU6229 \tDIVORCED\tNY \tM \tPROF-5\tNorthEast\t143427\tVERY HIGH\t2000\t7960\t6\t60029\t900\t0\nCU6008 \tMARRIED\tNY \tF \tPROF-5\tNorthEast\t1113\tLOW\t5000\t10300\t6\t68256\t2800\t0\nCU272 \tWIDOWED\tNV \tF \tPROF-5\tSouthwest\t0\tVERY HIGH\t5000\t19000\t1\t93562\t3500\t1\nCU1365 \tSINGLE\tMI \tM \tPROF-6\tMidwest\t0\tMEDIUM\t0\t0\t0\t65003\t500\t0\nCU2543 \tSINGLE\tNY \tM \tPROF-6\tNorthEast\t0\tMEDIUM\t0\t0\t0\t60677\t600\t0\nCU8776 \tSINGLE\tMI \tM \tPROF-6\tMidwest\t0\tMEDIUM\t0\t0\t0\t58031\t800\t0\nCU3574 \tSINGLE\tMI \tM \tPROF-6\tMidwest\t358\tMEDIUM\t500\t0\t6\t64325\t1200\t0\nCU5379 \tSINGLE\tMI \tF \tPROF-6\tMidwest\t0\tHIGH\t500\t0\t1\t62459\t500\t0\nCU2278 \tMARRIED\tNY \tM \tPROF-6\tNorthEast\t0\tHIGH\t700\t0\t0\t63769\t500\t0\nCU5256 \tMARRIED\tMI \tM \tPROF-6\tMidwest\t0\tHIGH\t700\t0\t3\t69543\t1000\t0\nCU6573 \tMARRIED\tMI \tM \tPROF-6\tMidwest\t61803\tMEDIUM\t800\t0\t3\t61759\t500\t0\nCU14309 \tMARRIED\tOH \tM \tPROF-6\tMidwest\t0\tHIGH\t1200\t0\t3\t61500\t2500\t0\nCU8703 \tMARRIED\tCA \tM \tPROF-6\tWest\t0\tHIGH\t1500\t0\t2\t59384\t1000\t0\nCU6538 \tDIVORCED\tMI \tM \tPROF-6\tMidwest\t0\tHIGH\t2500\t0\t0\t61439\t900\t0\nCU15761 \tMARRIED\tNY \tF \tPROF-6\tNorthEast\t0\tHIGH\t8000\t0\t1\t44678\t4000\t0\nCU12494 \tMARRIED\tCA \tM \tPROF-6\tWest\t0\tHIGH\t1241\t0\t6\t69990\t1500\t0\nCU4878 \tDIVORCED\tMI \tF \tPROF-6\tMidwest\t2198\tVERY HIGH\t1850\t0\t1\t67595\t1500\t0\nCU15758 \tSINGLE\tUT \tM \tPROF-6\tSouthwest\t0\tHIGH\t520\t300\t2\t71707\t1500\t0\nCU14672 \tMARRIED\tFL \tF \tPROF-6\tSouth\t0\tMEDIUM\t880\t500\t5\t51195\t2500\t0\nCU6385 \tSINGLE\tMI \tM \tPROF-6\tMidwest\t2576\tMEDIUM\t0\t800\t0\t60585\t600\t0\nCU3272 \tMARRIED\tNY \tM \tPROF-6\tNorthEast\t0\tMEDIUM\t1200\t1000\t3\t54636\t1500\t0\nCU4441 \tDIVORCED\tMI \tF \tPROF-6\tMidwest\t0\tMEDIUM\t2000\t1100\t3\t58000\t900\t1\nCU8553 \tSINGLE\tMI \tM \tPROF-6\tMidwest\t0\tMEDIUM\t0\t1200\t0\t63216\t800\t0\nCU12705 \tSINGLE\tCA \tM \tPROF-6\tWest\t0\tLOW\t0\t1600\t6\t62122\t600\t0\nCU5181 \tMARRIED\tMI \tM \tPROF-6\tMidwest\t0\tHIGH\t1600\t2200\t1\t64197\t1500\t1\nCU5761 \tSINGLE\tNY \tM \tPROF-6\tNorthEast\t0\tHIGH\t0\t4300\t0\t64861\t700\t0\nCU8606 \tDIVORCED\tDC \tM \tPROF-6\tNorthEast\t0\tHIGH\t3000\t250\t3\t73518\t1500\t0\nCU5323 \tSINGLE\tMI \tM \tPROF-6\tMidwest\t0\tMEDIUM\t0\t401\t0\t62099\t500\t0\nCU4917 \tSINGLE\tMI \tM \tPROF-6\tMidwest\t0\tMEDIUM\t600\t1070\t3\t58278\t900\t1\nCU1603 \tSINGLE\tNY \tM \tPROF-6\tNorthEast\t0\tMEDIUM\t0\t1603\t0\t58235\t800\t0\nCU13877 \tMARRIED\tMN \tF \tPROF-6\tWest\t0\tHIGH\t1451\t1750\t1\t63724\t700\t0\nCU6303 \tMARRIED\tNY \tM \tPROF-6\tNorthEast\t1100\tVERY HIGH\t1700\t2380\t3\t68871\t1500\t1\nCU8990 \tMARRIED\tNY \tF \tPROF-6\tNorthEast\t0\tHIGH\t1700\t2450\t1\t69003\t1000\t1\nCU2631 \tMARRIED\tMI \tM \tPROF-6\tMidwest\t30664\tHIGH\t1500\t3260\t1\t58421\t1500\t0\nCU105 \tWIDOWED\tFL \tM \tPROF-6\tSouth\t0\tHIGH\t12400\t3338\t3\t63016\t1500\t1\nCU5936 \tSINGLE\tCA \tF \tPROF-6\tWest\t0\tMEDIUM\t0\t6660\t1\t70290\t900\t0\nCU6283 \tMARRIED\tMI \tM \tPROF-6\tMidwest\t15823\tVERY HIGH\t6000\t16800\t1\t58688\t900\t1\nCU5202 \tMARRIED\tOH \tF \tPROF-6\tMidwest\t0\tMEDIUM\t5000\t12950\t4\t66890\t900\t1\nCU2173 \tSINGLE\tNY \tM \tPROF-7\tNorthEast\t0\tHIGH\t400\t0\t2\t64524\t900\t0\nCU12598 \tMARRIED\tNY \tM \tPROF-7\tNorthEast\t0\tHIGH\t800\t0\t3\t67415\t600\t0\nCU12543 \tMARRIED\tIL \tF \tPROF-7\tMidwest\t0\tHIGH\t1000\t0\t1\t59612\t700\t1\nCU12804 \tMARRIED\tNY \tM \tPROF-7\tNorthEast\t0\tHIGH\t1000\t0\t2\t64200\t700\t0\nCU13573 \tMARRIED\tNY \tM \tPROF-7\tNorthEast\t0\tHIGH\t1000\t0\t1\t71105\t1000\t0\nCU12699 \tMARRIED\tOR \tM \tPROF-7\tWest\t0\tMEDIUM\t1300\t0\t4\t61212\t1500\t0\nCU10783 \tMARRIED\tNY \tM \tPROF-7\tNorthEast\t0\tMEDIUM\t1500\t0\t3\t57384\t1500\t0\nCU7599 \tMARRIED\tNC \tF \tPROF-7\tSouth\t0\tMEDIUM\t1500\t0\t4\t55283\t1500\t0\nCU10321 \tDIVORCED\tNY \tM \tPROF-7\tNorthEast\t0\tMEDIUM\t2500\t0\t3\t65374\t1500\t0\nCU12391 \tDIVORCED\tMO \tM \tPROF-7\tMidwest\t0\tMEDIUM\t2600\t0\t3\t59725\t1000\t0\nCU11863 \tDIVORCED\tCA \tM \tPROF-7\tWest\t0\tMEDIUM\t3000\t0\t3\t58566\t1000\t0\nCU7381 \tDIVORCED\tOH \tM \tPROF-7\tMidwest\t0\tHIGH\t3000\t0\t0\t64586\t1500\t0\nCU5136 \tMARRIED\tNY \tM \tPROF-7\tNorthEast\t0\tHIGH\t1030\t0\t4\t67932\t900\t0\nCU7378 \tMARRIED\tFL \tM \tPROF-7\tSouth\t0\tHIGH\t1050\t0\t3\t54993\t1500\t0\nCU9819 \tMARRIED\tNY \tM \tPROF-7\tNorthEast\t0\tHIGH\t1084\t0\t1\t76214\t1500\t0\nCU13331 \tMARRIED\tNY \tF \tPROF-7\tNorthEast\t0\tMEDIUM\t1660\t0\t5\t66384\t1500\t0\nCU11844 \tMARRIED\tFL \tF \tPROF-7\tSouth\t0\tMEDIUM\t1781\t0\t5\t57330\t1000\t0\nCU10058 \tDIVORCED\tMN \tM \tPROF-7\tWest\t0\tHIGH\t2230\t0\t1\t70168\t1500\t0\nCU9913 \tMARRIED\tFL \tM \tPROF-7\tSouth\t0\tHIGH\t1000\t200\t3\t68223\t1000\t0\nCU12672 \tMARRIED\tMI \tF \tPROF-7\tMidwest\t0\tHIGH\t1350\t400\t1\t66765\t700\t0\nCU7683 \tMARRIED\tNY \tM \tPROF-7\tNorthEast\t0\tHIGH\t700\t500\t3\t73412\t2500\t1\nCU13298 \tMARRIED\tMI \tF \tPROF-7\tMidwest\t0\tHIGH\t1500\t500\t4\t62792\t1500\t1\nCU14385 \tMARRIED\tCA \tF \tPROF-7\tWest\t0\tHIGH\t1800\t900\t5\t69769\t1500\t0\nCU15182 \tMARRIED\tIL \tF \tPROF-7\tMidwest\t0\tLOW\t1000\t1000\t6\t57432\t1000\t1\nCU14350 \tMARRIED\tDC \tM \tPROF-7\tNorthEast\t0\tMEDIUM\t1500\t1500\t3\t68500\t1000\t0\nCU13971 \tMARRIED\tMI \tM \tPROF-7\tMidwest\t0\tHIGH\t1386\t1600\t1\t74132\t1500\t0\nCU15114 \tMARRIED\tFL \tF \tPROF-7\tSouth\t0\tMEDIUM\t1245\t1700\t5\t62792\t1500\t0\nCU12712 \tDIVORCED\tMI \tM \tPROF-7\tMidwest\t0\tMEDIUM\t2486\t2000\t3\t67365\t1500\t0\nCU11203 \tDIVORCED\tCA \tM \tPROF-7\tWest\t0\tLOW\t0\t2100\t3\t70474\t2000\t0\nCU8201 \tDIVORCED\tNY \tF \tPROF-7\tNorthEast\t0\tMEDIUM\t2000\t2700\t5\t74380\t1500\t0\nCU4443 \tDIVORCED\tFL \tM \tPROF-7\tSouth\t0\tHIGH\t3900\t3300\t1\t67357\t900\t0\nCU10903 \tDIVORCED\tDC \tM \tPROF-7\tNorthEast\t0\tLOW\t4500\t5800\t1\t72353\t3500\t0\nCU5887 \tDIVORCED\tNY \tF \tPROF-7\tNorthEast\t0\tHIGH\t3500\t7700\t1\t67148\t1500\t1\nCU6996 \tMARRIED\tNY \tF \tPROF-7\tNorthEast\t0\tHIGH\t6870\t9900\t1\t67660\t1500\t1\nCU9532 \tSINGLE\tMI \tM \tPROF-7\tMidwest\t0\tLOW\t0\t837\t0\t56336\t1500\t1\nCU9570 \tMARRIED\tCA \tM \tPROF-7\tWest\t0\tMEDIUM\t1100\t850\t3\t62575\t1500\t1\nCU13948 \tDIVORCED\tNY \tM \tPROF-7\tNorthEast\t0\tMEDIUM\t2650\t901\t3\t74234\t1500\t1\nCU13362 \tDIVORCED\tNY \tM \tPROF-7\tNorthEast\t36590\tMEDIUM\t2000\t950\t3\t65616\t2500\t0\nCU9503 \tDIVORCED\tNY \tM \tPROF-7\tNorthEast\t0\tMEDIUM\t2000\t1250\t3\t66735\t1000\t1\nCU13492 \tDIVORCED\tMI \tF \tPROF-7\tMidwest\t0\tHIGH\t1910\t1250\t1\t61329\t1000\t0\nCU7850 \tMARRIED\tMI \tM \tPROF-7\tMidwest\t0\tMEDIUM\t1700\t1550\t1\t59534\t1500\t1\nCU1061 \tSINGLE\tMI \tM \tPROF-7\tMidwest\t0\tMEDIUM\t0\t2156\t0\t73984\t1700\t0\nCU12578 \tDIVORCED\tIL \tM \tPROF-7\tMidwest\t0\tHIGH\t3500\t2190\t1\t68972\t1000\t0\nCU7273 \tMARRIED\tNY \tM \tPROF-7\tNorthEast\t0\tHIGH\t1700\t2201\t2\t67771\t1500\t0\nCU11275 \tDIVORCED\tDC \tF \tPROF-7\tNorthEast\t0\tHIGH\t3000\t2350\t1\t53883\t2500\t0\nCU11782 \tDIVORCED\tNY \tM \tPROF-7\tNorthEast\t0\tHIGH\t2500\t2450\t1\t58153\t1000\t0\nCU9039 \tMARRIED\tNY \tM \tPROF-7\tNorthEast\t0\tHIGH\t1804\t2601\t2\t64701\t800\t0\nCU6482 \tDIVORCED\tNY \tF \tPROF-7\tNorthEast\t0\tHIGH\t3200\t3250\t2\t77407\t2000\t1\nCU5071 \tDIVORCED\tNY \tF \tPROF-7\tNorthEast\t0\tHIGH\t2500\t4225\t1\t62112\t1000\t0\nCU14377 \tMARRIED\tNY \tF \tPROF-7\tNorthEast\t0\tHIGH\t5000\t4650\t1\t50020\t3000\t1\nCU6217 \tDIVORCED\tNY \tF \tPROF-7\tNorthEast\t0\tVERY HIGH\t3000\t7425\t1\t59247\t800\t1\nCU9320 \tMARRIED\tNY \tM \tPROF-8\tNorthEast\t0\tHIGH\t700\t0\t6\t66046\t800\t0\nCU11155 \tMARRIED\tNY \tF \tPROF-8\tNorthEast\t0\tHIGH\t1500\t0\t2\t62413\t1000\t0\nCU14910 \tDIVORCED\tNY \tF \tPROF-8\tNorthEast\t0\tHIGH\t2000\t0\t1\t63928\t1000\t0\nCU4976 \tDIVORCED\tCA \tM \tPROF-8\tWest\t0\tHIGH\t2000\t0\t1\t64506\t500\t0\nCU9918 \tDIVORCED\tMI \tF \tPROF-8\tMidwest\t0\tHIGH\t2000\t0\t1\t63406\t1000\t0\nCU10202 \tDIVORCED\tMI \tF \tPROF-8\tMidwest\t0\tHIGH\t2500\t0\t1\t66015\t1000\t0\nCU2843 \tDIVORCED\tMI \tM \tPROF-8\tMidwest\t0\tHIGH\t3000\t0\t3\t67581\t900\t0\nCU9572 \tDIVORCED\tNY \tF \tPROF-8\tNorthEast\t0\tHIGH\t3000\t0\t1\t72399\t1500\t0\nCU10124 \tWIDOWED\tMI \tF \tPROF-8\tMidwest\t0\tHIGH\t5000\t0\t3\t58743\t800\t0\nCU10666 \tMARRIED\tNY \tM \tPROF-8\tNorthEast\t0\tMEDIUM\t5500\t0\t5\t78521\t3500\t0\nCU13616 \tMARRIED\tMI \tF \tPROF-8\tMidwest\t0\tVERY HIGH\t6200\t0\t1\t82278\t3500\t0\nCU10515 \tWIDOWED\tNY \tF \tPROF-8\tNorthEast\t0\tHIGH\t7500\t0\t5\t76015\t5000\t0\nCU12166 \tMARRIED\tCA \tM \tPROF-8\tWest\t0\tLOW\t8000\t0\t5\t49708\t5000\t0\nCU4975 \tMARRIED\tCA \tF \tPROF-8\tWest\t0\tHIGH\t847\t0\t1\t64528\t900\t0\nCU14111 \tMARRIED\tNY \tM \tPROF-8\tNorthEast\t0\tLOW\t1520\t0\t1\t63500\t1000\t0\nCU7064 \tDIVORCED\tUT \tF \tPROF-8\tSouthwest\t0\tHIGH\t2560\t0\t4\t74422\t2200\t0\nCU10894 \tMARRIED\tNY \tF \tPROF-8\tNorthEast\t0\tHIGH\t1600\t1000\t1\t65401\t1000\t0\nCU14773 \tMARRIED\tCO \tF \tPROF-8\tWest\t0\tHIGH\t1800\t1500\t5\t66225\t1500\t0\nCU12930 \tMARRIED\tAK \tM \tPROF-8\tWest\t0\tHIGH\t1500\t1600\t3\t57377\t1500\t1\nCU15049 \tDIVORCED\tFL \tM \tPROF-8\tSouth\t0\tMEDIUM\t4000\t2000\t5\t64514\t1000\t1\nCU15439 \tDIVORCED\tNV \tM \tPROF-8\tSouthwest\t0\tHIGH\t2500\t2100\t1\t56541\t1500\t1\nCU9078 \tDIVORCED\tNY \tF \tPROF-8\tNorthEast\t0\tMEDIUM\t4000\t2300\t5\t67844\t1500\t1\nCU12021 \tDIVORCED\tCA \tM \tPROF-8\tWest\t0\tHIGH\t4500\t2400\t5\t65707\t3000\t1\nCU11133 \tDIVORCED\tNY \tM \tPROF-8\tNorthEast\t0\tHIGH\t3000\t2700\t3\t67955\t1000\t0\nCU200 \tWIDOWED\tMN \tM \tPROF-8\tWest\t0\tHIGH\t10000\t4000\t0\t59952\t1400\t0\nCU6713 \tDIVORCED\tMI \tF \tPROF-8\tMidwest\t0\tHIGH\t2800\t4400\t1\t56024\t1500\t1\nCU10499 \tWIDOWED\tNY \tF \tPROF-8\tNorthEast\t0\tMEDIUM\t5000\t4800\t5\t59614\t3000\t1\nCU12732 \tDIVORCED\tMI \tF \tPROF-8\tMidwest\t0\tMEDIUM\t4000\t6000\t1\t55744\t2000\t0\nCU7150 \tMARRIED\tCA \tF \tPROF-8\tWest\t0\tHIGH\t10000\t7300\t1\t74836\t1500\t0\nCU12917 \tMARRIED\tNY \tF \tPROF-8\tNorthEast\t0\tHIGH\t6500\t1050\t1\t77429\t5000\t0\nCU13107 \tDIVORCED\tNY \tM \tPROF-8\tNorthEast\t0\tMEDIUM\t1917\t1250\t1\t60472\t1500\t1\nCU13335 \tDIVORCED\tCA \tM \tPROF-8\tWest\t0\tHIGH\t3000\t2350\t4\t63755\t1500\t0\nCU6931 \tDIVORCED\tNY \tF \tPROF-8\tNorthEast\t0\tVERY HIGH\t2000\t4090\t1\t64905\t900\t1\nCU1870 \tDIVORCED\tNY \tF \tPROF-8\tNorthEast\t0\tMEDIUM\t2500\t4350\t4\t67653\t800\t1\nCU566 \tDIVORCED\tMI \tF \tPROF-8\tMidwest\t0\tVERY HIGH\t4000\t4501\t1\t80164\t2600\t1\nCU10530 \tDIVORCED\tNY \tF \tPROF-8\tNorthEast\t0\tHIGH\t4500\t10300\t1\t60259\t1500\t0\nCU7282 \tDIVORCED\tDC \tF \tPROF-8\tNorthEast\t0\tHIGH\t4000\t11500\t1\t68888\t900\t0\nCU4978 \tMARRIED\tNY \tF \tPROF-8\tNorthEast\t0\tHIGH\t10000\t25000\t1\t64301\t1500\t0\nCU188 \tSINGLE\tMN \tM \tPROF-9\tWest\t0\tLOW\t0\t0\t0\t59896\t900\t0\nCU15855 \tMARRIED\tNY \tF \tPROF-9\tNorthEast\t0\tHIGH\t1000\t0\t5\t73592\t2500\t0\nCU3155 \tMARRIED\tOH \tF \tPROF-9\tMidwest\t0\tHIGH\t1500\t0\t1\t65832\t500\t0\nCU10652 \tDIVORCED\tNY \tF \tPROF-9\tNorthEast\t0\tMEDIUM\t2000\t0\t5\t67635\t1000\t0\nCU4678 \tDIVORCED\tNY \tM \tPROF-9\tNorthEast\t0\tVERY HIGH\t2600\t0\t0\t61847\t500\t0\nCU11102 \tDIVORCED\tNY \tF \tPROF-9\tNorthEast\t0\tMEDIUM\t4000\t0\t6\t71936\t1000\t0\nCU7108 \tWIDOWED\tNY \tM \tPROF-9\tNorthEast\t0\tHIGH\t10000\t0\t1\t65875\t900\t0\nCU5394 \tDIVORCED\tCA \tM \tPROF-9\tWest\t0\tHIGH\t2931\t0\t3\t63736\t1200\t0\nCU1880 \tSINGLE\tCA \tM \tPROF-9\tWest\t0\tMEDIUM\t0\t900\t0\t63163\t600\t0\nCU10656 \tDIVORCED\tCA \tF \tPROF-9\tWest\t0\tVERY HIGH\t2000\t1000\t1\t59529\t1000\t0\nCU11623 \tMARRIED\tMI \tM \tPROF-9\tMidwest\t0\tMEDIUM\t1500\t1500\t3\t75266\t1500\t1\nCU372 \tMARRIED\tCA \tM \tPROF-9\tWest\t0\tMEDIUM\t1150\t2000\t3\t61732\t900\t0\nCU14238 \tDIVORCED\tNY \tF \tPROF-9\tNorthEast\t0\tVERY HIGH\t2900\t2300\t1\t61311\t1500\t1\nCU4679 \tDIVORCED\tCA \tM \tPROF-9\tWest\t0\tHIGH\t3063\t2900\t1\t60271\t900\t1\nCU184 \tDIVORCED\tDC \tF \tPROF-9\tNorthEast\t53452\tHIGH\t4640\t7900\t1\t57590\t1000\t0\nCU4671 \tMARRIED\tCA \tF \tPROF-9\tWest\t1709\tMEDIUM\t5740\t9500\t2\t63130\t3500\t0\nCU9395 \tMARRIED\tIL \tM \tPROF-9\tMidwest\t0\tHIGH\t1300\t1150\t1\t68099\t700\t1\nCU10952 \tDIVORCED\tOH \tF \tPROF-9\tMidwest\t0\tVERY HIGH\t2100\t1450\t1\t74869\t1500\t1\nCU648 \tSINGLE\tNY \tM \tPROF-9\tNorthEast\t0\tMEDIUM\t0\t1801\t0\t63509\t500\t1\nCU7641 \tDIVORCED\tNY \tF \tPROF-9\tNorthEast\t0\tHIGH\t3022\t2150\t2\t84590\t2500\t1\nCU15174 \tDIVORCED\tFL \tF \tPROF-9\tSouth\t0\tMEDIUM\t2500\t2250\t5\t58262\t1500\t1\nCU14273 \tDIVORCED\tDC \tM \tPROF-9\tNorthEast\t0\tHIGH\t2700\t2280\t1\t62698\t1500\t1\nCU3711 \tDIVORCED\tFL \tM \tPROF-9\tSouth\t0\tHIGH\t2500\t3950\t3\t70925\t900\t0\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_1007414104","id":"20210803-141850_1597557903","dateCreated":"2021-06-24T21:27:47+0000","dateStarted":"2021-07-28T17:05:35+0000","dateFinished":"2021-07-28T17:05:41+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:53"},{"title":"Score and compute AUC without materializing the table","text":"%python\r\n\r\nsrc = '''\r\ndef score_auc(table_name, model_name, target):\r\n import oml\r\n cr = oml.cursor()\r\n query_template = \"\"\"\r\n WITH\r\npos_prob_and_counts AS (\r\nSELECT PREDICTION_PROBABILITY(, 1 USING *) pos_prob,\r\n DECODE(, 1, 1, 0) pos_cnt\r\n FROM \r\n),\r\ntpf_fpf AS (\r\nSELECT pos_cnt,\r\n SUM(pos_cnt) OVER (ORDER BY pos_prob DESC) /\r\n SUM(pos_cnt) OVER () tpf,\r\n SUM(1 - pos_cnt) OVER (ORDER BY pos_prob DESC) /\r\n SUM(1 - pos_cnt) OVER () fpf\r\n FROM pos_prob_and_counts\r\n),\r\ntrapezoid_areas AS (\r\nSELECT 0.5 * (fpf - LAG(fpf, 1, 0) OVER (ORDER BY fpf, tpf)) *\r\n (tpf + LAG(tpf, 1, 0) OVER (ORDER BY fpf, tpf)) area\r\n FROM tpf_fpf\r\n WHERE pos_cnt = 1\r\n OR (tpf = 1 AND fpf = 1)\r\n)\r\nSELECT SUM(area) auc\r\nFROM trapezoid_areas\"\"\"\r\n \r\n query = query_template.replace('', model_name)\r\n query = query.replace('', target)\r\n query = query.replace('
', table_name)\r\n \r\n _ = cr.execute(query)\r\n auc = cr.fetchall()\r\n cr.close()\r\n return auc[0][0]'''\r\n \r\noml.script.create('score_auc', src, is_global = True, overwrite = True)","user":"JIE","dateUpdated":"2021-07-20T17:26:09+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_2133465174","id":"20210803-141850_1623487692","dateCreated":"2021-07-20T17:08:35+0000","dateStarted":"2021-07-20T17:18:15+0000","dateFinished":"2021-07-20T17:18:15+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:54"},{"title":"Data sync, train and test function for one fold","text":"%python\r\n\r\n\r\ndef train_helper(X_train, y_train, case_id, model_name):\r\n setting = {}\r\n glm_mod = oml.glm(\"classification\", **setting)\r\n glm_mod.fit(X_train, y_train, case_id=case_id, model_name=model_name)\r\n \r\n\r\ndef train_test_timed_oml(idx, \r\n pairs, \r\n train_helper, \r\n auc_data_store, \r\n prefix=\"GLM_MDL\", \r\n case_id='CUSTOMER_ID', \r\n target='BUY_INSURANCE'):\r\n \r\n import oml\r\n import random\r\n import time\r\n import pandas as pd\r\n from datetime import datetime\r\n score_auc = oml.script.load('score_auc')\r\n time_df = pd.DataFrame(\r\n columns=['START', 'END', 'DURATION', 'JOB_TYPE', 'JOB_ID'])\r\n \r\n def ts_now():\r\n return datetime.now().strftime(\"%Y-%m-%d %H:%M:%S.%f\")\r\n\r\n model_name = prefix + '_' + str(idx)\r\n try:\r\n oml.drop(model=model_name)\r\n except:\r\n print(model_name + \" not found\")\r\n\r\n start_time = ts_now()\r\n\r\n start = time.perf_counter()\r\n TRAIN_DF = pairs[idx-1][0]\r\n\r\n TEST_DF = pairs[idx-1][1]\r\n \r\n end = time.perf_counter()\r\n \r\n end_time = ts_now()\r\n \r\n print(f'Pull() finished in {round(end -start, 2)} second(s) for job {idx}')\r\n \r\n time_df = time_df.append({'START': start_time, \r\n 'END': end_time, \r\n 'DURATION': end - start, \r\n 'JOB_TYPE': 'pull', \r\n 'JOB_ID': idx}, ignore_index=True)\r\n \r\n start_time = ts_now()\r\n \r\n start = time.perf_counter()\r\n \r\n features = ['CREDIT_BALANCE', 'MORTGAGE_AMOUNT', \r\n 'BANK_FUNDS', 'NUM_DEPENDENTS', 'INCOME', 'CREDIT_CARD_LIMITS', \r\n 'PROFESSION', 'REGION', 'GENDER', 'STATE', 'MARITAL_STATUS']\r\n \r\n X_train = TRAIN_DF[['CUSTOMER_ID'] + features]\r\n y_train = TRAIN_DF[['BUY_INSURANCE']]\r\n \r\n train_helper(X_train, y_train, case_id, model_name)\r\n \r\n end = time.perf_counter()\r\n end_time = ts_now()\r\n \r\n print(f'Training finished in {round(end -start, 2)} second(s) for job {idx}')\r\n time_df = time_df.append({'START': start_time, \r\n 'END': end_time, \r\n 'DURATION': end - start, \r\n 'JOB_TYPE': 'train', \r\n 'JOB_ID': idx}, ignore_index=True)\r\n \r\n start_time = ts_now()\r\n \r\n start = time.perf_counter()\r\n \r\n \r\n test_v = 'TEST_V_' + str(idx)\r\n \r\n try:\r\n oml.drop(view = test_v)\r\n except:\r\n pass\r\n _ = TEST_DF.create_view(view = test_v)\r\n \r\n\r\n auc = score_auc(test_v, model_name, target)\r\n \r\n end_time = ts_now()\r\n \r\n end = time.perf_counter()\r\n print(\r\n f'Scoring and metric finished in {round(end -start, 2)} second(s) for job {idx}')\r\n time_df = time_df.append({'START': start_time, \r\n 'END': end_time, \r\n 'DURATION': end - start, \r\n 'JOB_TYPE': 'score', \r\n 'JOB_ID': idx}, ignore_index=True)\r\n \r\n oml.ds.save({'auc' + str(idx): auc}, \r\n name = auc_data_store, \r\n description='', \r\n grantable=False, \r\n overwrite=False, \r\n append=True)\r\n\r\n try:\r\n oml.drop(table='RECORD_DF_' + str(idx))\r\n except:\r\n pass\r\n \r\n _ = oml.create(time_df, table='RECORD_DF_' + str(idx))\r\n\r\n return auc\r\n","user":"JIE","dateUpdated":"2021-08-03T14:44:42+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_726551915","id":"20210803-141850_1604233165","dateCreated":"2021-07-01T15:39:40+0000","dateStarted":"2021-08-03T14:20:19+0000","dateFinished":"2021-08-03T14:20:19+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:55"},{"title":"Test single run","text":"%python\n\ntry:\n oml.ds.delete('auc_result_oml')\nexcept:\n pass\n \ntrain_test_timed_oml(1, pairs, train_helper, auc_data_store = 'auc_result_oml')","user":"JIE","dateUpdated":"2021-08-03T15:42:01+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"Pull() finished in 0.0 second(s) for job 1\nTraining finished in 4.6 second(s) for job 1\nScoring and metric finished in 0.3 second(s) for job 1\n0.7233668422404933\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_-494892781","id":"20210803-141850_1068006","dateCreated":"2021-07-13T18:59:21+0000","dateStarted":"2021-07-29T17:55:10+0000","dateFinished":"2021-07-29T17:55:17+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:56"},{"title":"Combine data and processing for plotting","text":"%python\r\n\r\ndef combine_plot(table_name, num):\r\n RECORD_DF = oml.sync(table = table_name + '_1')\r\n \r\n for i in range(2, num + 1):\r\n RECORD_DF = RECORD_DF.append(\r\n oml.sync(table = table_name + '_' + str(i)))\r\n \r\n \r\n record_df = RECORD_DF.pull()\r\n \r\n record_df['START'] = pd.to_datetime(record_df['START'], \r\n format=\"%Y-%m-%d %H:%M:%S.%f\")\r\n record_df['END'] = pd.to_datetime(record_df['END'], \r\n format=\"%Y-%m-%d %H:%M:%S.%f\")\r\n \r\n return record_df\r\n\r\n \r\ndef plot_sub(record_df, job_types, ax, max_range):\r\n min_start = min(record_df['START'].values)\r\n for job_type in job_types:\r\n plot_df = record_df[record_df['JOB_TYPE'] == job_type]\r\n start = np.array(plot_df['START'].values)\r\n end = np.array(plot_df['END'].values) \r\n #start_s = (start - min_start)*1.0/(10**9)\r\n #start_s = [ s.item()*1.0 for s in start_s]\r\n start_s = (start - min_start)\r\n \r\n start_s = [s/ np.timedelta64(1, 's') for s in start_s]\r\n \r\n duration = (end - start)\r\n duration = [d/ np.timedelta64(1, 's') for d in duration]\r\n \r\n y = np.array(plot_df['JOB_ID'].values)\r\n y = [ str(s) for s in y]\r\n ax.barh(y, width = duration, left=start_s, \r\n label = job_type, color = colors[job_type])\r\n \r\n \r\n ax.set_xlim(0, max_range)\r\n \r\n ax.legend(ncol=len(job_types), bbox_to_anchor=(0, 1),\r\n loc='lower left', fontsize='medium')\r\n \r\n ax.grid(axis='x', color = '0.9')\r\n \r\n ax.set(xlabel='Time (second) ', ylabel='Job ID')\r\n ","user":"JIE","dateUpdated":"2021-08-03T14:20:26+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_-697545819","id":"20210803-141850_425042911","dateCreated":"2021-07-01T15:38:09+0000","dateStarted":"2021-08-03T14:20:27+0000","dateFinished":"2021-08-03T14:20:28+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:57"},{"title":"Parallel run for building OML in database generalized linear model","text":"%python\n\ntry:\n oml.ds.delete('auc_result_oml')\nexcept:\n pass\n \nres = oml.index_apply(times=10, func=train_test_timed_oml, func_value = None, func_owner=None, parallel =8, graphics = False, oml_connect=True, pairs = pairs, train_helper = train_helper, auc_data_store = 'auc_result_oml')\nindex_df = combine_plot('RECORD_DF', 10) \n","user":"JIE","dateUpdated":"2021-08-03T14:20:33+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"Pull() finished in 0.0 second(s) for job 4\nPull() finished in 0.0 second(s) for job 1\nPull() finished in 0.0 second(s) for job 3\nPull() finished in 0.0 second(s) for job 2\nTraining finished in 8.41 second(s) for job 2\nTraining finished in 8.43 second(s) for job 3\nTraining finished in 8.48 second(s) for job 1\nScoring and metric finished in 0.4 second(s) for job 1\nScoring and metric finished in 0.46 second(s) for job 2\nScoring and metric finished in 0.46 second(s) for job 3\nTraining finished in 12.09 second(s) for job 4\nPull() finished in 0.0 second(s) for job 5\nPull() finished in 0.0 second(s) for job 6\nPull() finished in 0.0 second(s) for job 7\nScoring and metric finished in 3.01 second(s) for job 4\nTraining finished in 5.79 second(s) for job 6\nScoring and metric finished in 0.3 second(s) for job 6\nTraining finished in 6.29 second(s) for job 5\nTraining finished in 6.17 second(s) for job 7\nScoring and metric finished in 0.37 second(s) for job 5\nScoring and metric finished in 0.42 second(s) for job 7\nPull() finished in 0.0 second(s) for job 8\nPull() finished in 0.0 second(s) for job 10\nPull() finished in 0.0 second(s) for job 9\nTraining finished in 6.6 second(s) for job 8\nScoring and metric finished in 0.36 second(s) for job 8\nTraining finished in 6.24 second(s) for job 10\nScoring and metric finished in 0.34 second(s) for job 10\nTraining finished in 6.82 second(s) for job 9\nScoring and metric finished in 0.53 second(s) for job 9\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_-804380550","id":"20210803-141850_1525995053","dateCreated":"2021-07-01T15:43:20+0000","dateStarted":"2021-08-03T14:20:34+0000","dateFinished":"2021-08-03T14:21:12+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:58"},{"title":"Serial run for building OML in database generalized linear model","text":"%python\n\n\ntry:\n oml.ds.delete('auc_result_oml')\nexcept:\n pass\n \nfor i in range(1, 11):\n train_test_timed_oml(i, pairs, train_helper, auc_data_store = 'auc_result_oml')\nseries_df = combine_plot('RECORD_DF', 10) ","user":"JIE","dateUpdated":"2021-08-03T14:21:28+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"Pull() finished in 0.0 second(s) for job 1\nTraining finished in 6.66 second(s) for job 1\nScoring and metric finished in 0.21 second(s) for job 1\nPull() finished in 0.0 second(s) for job 2\nTraining finished in 7.33 second(s) for job 2\nScoring and metric finished in 0.22 second(s) for job 2\nPull() finished in 0.0 second(s) for job 3\nTraining finished in 4.2 second(s) for job 3\nScoring and metric finished in 0.19 second(s) for job 3\nPull() finished in 0.0 second(s) for job 4\nTraining finished in 7.18 second(s) for job 4\nScoring and metric finished in 0.19 second(s) for job 4\nPull() finished in 0.0 second(s) for job 5\nTraining finished in 8.2 second(s) for job 5\nScoring and metric finished in 0.26 second(s) for job 5\nPull() finished in 0.0 second(s) for job 6\nTraining finished in 6.83 second(s) for job 6\nScoring and metric finished in 0.33 second(s) for job 6\nPull() finished in 0.0 second(s) for job 7\nTraining finished in 6.62 second(s) for job 7\nScoring and metric finished in 0.2 second(s) for job 7\nPull() finished in 0.0 second(s) for job 8\nTraining finished in 7.72 second(s) for job 8\nScoring and metric finished in 0.21 second(s) for job 8\nPull() finished in 0.0 second(s) for job 9\nTraining finished in 6.65 second(s) for job 9\nScoring and metric finished in 0.19 second(s) for job 9\nPull() finished in 0.0 second(s) for job 10\nTraining finished in 9.22 second(s) for job 10\nScoring and metric finished in 0.23 second(s) for job 10\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_1314429802","id":"20210803-141850_1895735921","dateCreated":"2021-07-01T15:36:09+0000","dateStarted":"2021-08-03T14:21:29+0000","dateFinished":"2021-08-03T14:23:05+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:59"},{"title":"Generate the plot","text":"%python\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ncolors = {'pull': 'green', 'train': 'orange', 'score': 'cyan'}\n\n\nfig, axs = plt.subplots(2, figsize=(15, 10))\n\njob_types = ['pull', 'train', 'score']\n\nmin_start = min(index_df['START'].values)\nmax_end = max(index_df['END'].values)\nmax_range = (max_end - min_start).item()/10**9\n\n\nmin_start = min(series_df['START'].values) \nmax_end = max(series_df['END'].values)\n\nmax_range = max(max_range, (max_end - min_start).item()/10**9)\n\n\nplt.style.use('seaborn-whitegrid')\n\nplot_sub(index_df, job_types, axs[0], max_range)\n\naxs[0].set_title('Paralleled Run',fontweight=\"bold\", size=20) # Title\n\nplot_sub(series_df, job_types, axs[1], max_range)\n\naxs[1].set_title('Serial Run',fontweight=\"bold\", size=20) # Title\n#plt.ylabel('Job ID', fontsize=20)\n#plt.xlabel('Time (second)', fontsize=20)\n\n#plt.rcParams[\"font.size\"] = \"10\"\n\nplt.show() ","user":"JIE","dateUpdated":"2021-08-03T14:23:52+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true,"editorHide":false},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"HTML","data":"
\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_-1656231330","id":"20210803-141850_1915984115","dateCreated":"2021-07-01T15:42:32+0000","dateStarted":"2021-08-03T14:23:53+0000","dateFinished":"2021-08-03T14:24:04+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:60"},{"title":"Try a decision tree model and compare it to GLM model","text":"%python\n\n\ndef train_helper(X_train, y_train, case_id, model_name):\n settings = {}\n dt_mod = oml.dt(**settings)\n dt_mod.fit(X_train, y_train, case_id=case_id, model_name=model_name)\n ","user":"JIE","dateUpdated":"2021-07-28T17:12:25+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_1812354371","id":"20210803-141850_1187812913","dateCreated":"2021-06-30T21:21:28+0000","dateStarted":"2021-07-28T17:12:26+0000","dateFinished":"2021-07-28T17:12:26+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:61"},{"title":"Run the decision tree model in parallel","text":"%python\ntry:\n oml.ds.delete('auc_result_dt')\nexcept:\n pass\nres = oml.index_apply(times=10, func=train_test_timed_oml, oml_connect=True, \n graphics = False, parallel =8, pairs = pairs, \n train_helper = train_helper, auc_data_store = 'auc_result_dt')\n","user":"JIE","dateUpdated":"2021-07-29T18:09:13+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"Pull() finished in 0.0 second(s) for job 3Pull() finished in 0.0 second(s) for job 1\n\nPull() finished in 0.0 second(s) for job 2\nPull() finished in 0.0 second(s) for job 4\nTraining finished in 7.05 second(s) for job 1\nTraining finished in 7.22 second(s) for job 4\nScoring and metric finished in 0.27 second(s) for job 1\nTraining finished in 7.28 second(s) for job 2\nTraining finished in 7.48 second(s) for job 3\nScoring and metric finished in 0.27 second(s) for job 2\nScoring and metric finished in 0.35 second(s) for job 4\nScoring and metric finished in 0.25 second(s) for job 3\nPull() finished in 0.0 second(s) for job 5\nPull() finished in 0.0 second(s) for job 6\nPull() finished in 0.0 second(s) for job 7\nPull() finished in 0.0 second(s) for job 8\nTraining finished in 4.82 second(s) for job 5\nScoring and metric finished in 0.23 second(s) for job 5\nTraining finished in 4.77 second(s) for job 7\nScoring and metric finished in 0.29 second(s) for job 7\nTraining finished in 5.55 second(s) for job 8\nTraining finished in 5.76 second(s) for job 6\nPull() finished in 0.0 second(s) for job 9\nScoring and metric finished in 0.27 second(s) for job 8\nScoring and metric finished in 0.28 second(s) for job 6\nPull() finished in 0.0 second(s) for job 10\nTraining finished in 4.53 second(s) for job 9\nScoring and metric finished in 0.23 second(s) for job 9\nTraining finished in 4.36 second(s) for job 10\nScoring and metric finished in 0.17 second(s) for job 10\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_-739427870","id":"20210803-141850_989160827","dateCreated":"2021-06-29T17:10:08+0000","dateStarted":"2021-07-28T17:12:30+0000","dateFinished":"2021-07-28T17:12:52+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:62"},{"title":"Check the data store","text":"%python\n\noml.ds.dir()","user":"JIE","dateUpdated":"2021-07-28T17:09:33+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":" datastore_name object_count size date description\n0 auc_result 1 5 2021-06-30 19:56:54 None\n1 auc_result_dt 10 210 2021-07-28 17:08:26 None\n2 auc_result_glm 10 210 2021-07-20 19:55:38 None\n3 auc_result_oml 10 210 2021-07-27 20:07:27 None\n4 ds_nyc 1 255 2021-03-18 14:47:06 nyc in cluster sum\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_-451162825","id":"20210803-141850_1067296126","dateCreated":"2021-06-30T19:57:00+0000","dateStarted":"2021-07-28T17:09:34+0000","dateFinished":"2021-07-28T17:09:35+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:63"},{"title":"Compute mean and variance of the AUC obtained","text":"%python\nauc_stats = oml.ds.load('auc_result_dt', to_globals = False)\nauc_list = list(auc_stats.values())\n\nprint(np.mean(auc_list))\nprint(np.sqrt(np.var(auc_list)))","user":"JIE","dateUpdated":"2021-07-28T17:13:23+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"0.8100430137893395\n0.010346438944890627\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_-530810149","id":"20210803-141850_1359431294","dateCreated":"2021-06-30T20:31:55+0000","dateStarted":"2021-07-28T17:13:24+0000","dateFinished":"2021-07-28T17:13:26+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:64"},{"title":"Boxplot of the AUC results","text":"%python\n\nnp.random.seed(1234)\ndf = pd.DataFrame({'AUC_DT': auc_list})\nboxplot = df.boxplot(column=['AUC_DT'])","user":"JIE","dateUpdated":"2021-07-28T17:13:29+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"HTML","data":"
\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_1482381066","id":"20210803-141850_1935163249","dateCreated":"2021-07-01T14:28:54+0000","dateStarted":"2021-07-28T17:13:30+0000","dateFinished":"2021-07-28T17:13:32+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:65"},{"title":"Repeat for GLM model","text":"%python\r\n\r\ndef train_helper(X_train, y_train, case_id, model_name):\r\n setting = {}\r\n glm_mod = oml.glm(\"classification\", **setting)\r\n glm_mod.fit(X_train, y_train, case_id=case_id, model_name=model_name)\r\n \r\n ","user":"JIE","dateUpdated":"2021-07-28T17:11:33+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_1442519509","id":"20210803-141850_1645691612","dateCreated":"2021-06-24T21:20:08+0000","dateStarted":"2021-07-28T17:11:34+0000","dateFinished":"2021-07-28T17:11:34+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:66"},{"title":"Run the generalized linear model in parallel","text":"%python\ntry:\n oml.ds.delete('auc_result_glm')\nexcept:\n pass\nres = oml.index_apply(times=10, func=train_test_timed_oml, oml_connect=True, \n parallel =8, pairs = pairs, train_helper = train_helper, auc_data_store = 'auc_result_glm')\n","user":"JIE","dateUpdated":"2021-07-29T18:09:22+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"Pull() finished in 0.0 second(s) for job 2\nPull() finished in 0.0 second(s) for job 1\nPull() finished in 0.0 second(s) for job 3\nPull() finished in 0.0 second(s) for job 4\nTraining finished in 3.62 second(s) for job 4\nTraining finished in 3.84 second(s) for job 2\nTraining finished in 3.83 second(s) for job 3\nTraining finished in 3.9 second(s) for job 1\nScoring and metric finished in 0.21 second(s) for job 4\nScoring and metric finished in 0.22 second(s) for job 2\nScoring and metric finished in 0.26 second(s) for job 3\nScoring and metric finished in 0.22 second(s) for job 1\nPull() finished in 0.0 second(s) for job 5\nPull() finished in 0.0 second(s) for job 6\nPull() finished in 0.0 second(s) for job 7\nPull() finished in 0.0 second(s) for job 8\nTraining finished in 3.88 second(s) for job 5\nTraining finished in 3.41 second(s) for job 7\nScoring and metric finished in 0.22 second(s) for job 5\nTraining finished in 3.43 second(s) for job 8\nTraining finished in 3.5 second(s) for job 6\nScoring and metric finished in 0.23 second(s) for job 7\nScoring and metric finished in 0.19 second(s) for job 8\nScoring and metric finished in 0.22 second(s) for job 6\nPull() finished in 0.0 second(s) for job 9\nPull() finished in 0.0 second(s) for job 10\nTraining finished in 3.25 second(s) for job 10\nTraining finished in 3.49 second(s) for job 9\nScoring and metric finished in 0.22 second(s) for job 10\nScoring and metric finished in 0.22 second(s) for job 9\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_-1319003105","id":"20210803-141850_821276085","dateCreated":"2021-06-30T19:43:43+0000","dateStarted":"2021-07-28T17:11:37+0000","dateFinished":"2021-07-28T17:11:55+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:67"},{"title":"Compute the mean of variance of the result","text":"%python\nauc_stats = oml.ds.load('auc_result_glm', to_globals = False)\nauc_list = list(auc_stats.values())\n\nprint(np.mean(auc_list))\nprint(np.sqrt(np.var(auc_list)))\n","user":"JIE","dateUpdated":"2021-07-28T17:13:49+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"0.7023661799700494\n0.013563761129354304\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_1356349248","id":"20210803-141850_1529620835","dateCreated":"2021-06-30T19:39:32+0000","dateStarted":"2021-07-28T17:13:50+0000","dateFinished":"2021-07-28T17:13:50+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:68"},{"title":"Comparison of two approaches. Decision Tree achieves higher AUC and low variance","text":"%python\n\ndf['AUC_GLM'] = auc_list\nax = boxplot = df.boxplot(column=['AUC_DT', 'AUC_GLM'])\n#_ = ax.set_ylim(0, 1)\n","user":"JIE","dateUpdated":"2021-07-28T17:13:53+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"HTML","data":"
\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_1325857359","id":"20210803-141850_1774003904","dateCreated":"2021-07-01T15:05:00+0000","dateStarted":"2021-07-28T17:13:54+0000","dateFinished":"2021-07-28T17:13:57+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:69"},{"title":"Obtain a larger dataset by duplicating the records, used for performance test later","text":"%python\n\nCUST_SUBSET_DF = oml.sync(table = 'CUST_SUBSET_TBL')\n\nDF = CUST_SUBSET_DF\nfor i in range(1,10):\n DF = DF.append(CUST_SUBSET_DF)\n\ntry:\n oml.drop(table = 'CUST_SUBSET_TBL10')\nexcept:\n print(\"No such table\")\nDF = DF.materialize(table = 'CUST_SUBSET_TBL10') ","user":"JIE","dateUpdated":"2021-07-12T19:57:40+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_-864210228","id":"20210803-141850_828676233","dateCreated":"2021-04-28T14:54:14+0000","dateStarted":"2021-06-30T20:55:00+0000","dateFinished":"2021-06-30T20:55:05+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:70"},{"title":"Create 10-Fold CV for the enlarged dataset","text":"%python\n\nDF = oml.sync(table = 'CUST_SUBSET_TBL10')\n#DF = oml.sync(table = 'CUST_SUBSET_TBL')\n\nfold = 10\npairs = DF.KFold(n_splits = fold)\n\n","user":"JIE","dateUpdated":"2021-07-28T18:40:41+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_1266639743","id":"20210803-141850_475464981","dateCreated":"2021-04-27T18:11:53+0000","dateStarted":"2021-07-28T18:40:42+0000","dateFinished":"2021-07-28T18:40:45+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:71"},{"title":"Function to pull, train and test the data using open source sklearn models","text":"%python\n\ndef train_rf(X_train, y_train):\n from sklearn.ensemble import RandomForestClassifier\n clf = RandomForestClassifier(n_jobs = 1)\n clf.fit(X_train, y_train)\n return clf\n\ndef train_gbm(X_train, y_train):\n from sklearn.ensemble import GradientBoostingClassifier\n clf = GradientBoostingClassifier(n_estimators=100, \n learning_rate=1.0, max_depth=1, random_state=0)\n clf.fit(X_train, y_train)\n return clf\n\ndef build_open_src(idx, pairs, train_helper):\n import oml\n import random\n import time\n import pandas as pd\n\n from datetime import datetime\n\n from sklearn.neural_network import MLPClassifier\n from sklearn.linear_model import LogisticRegression\n from sklearn.ensemble import RandomForestClassifier\n from sklearn.svm import NuSVC\n from sklearn.ensemble import GradientBoostingClassifier\n from sklearn.metrics import roc_auc_score\n \n time_df = pd.DataFrame(columns = ['START', 'END', \n 'DURATION', 'JOB_TYPE', 'JOB_ID'])\n\n def ts_now():\n return datetime.now().strftime(\"%Y-%m-%d %H:%M:%S.%f\") \n \n \n start_time = ts_now()\n \n start = time.perf_counter()\n train_dat = pairs[idx-1][0].pull()\n test_dat = pairs[idx-1][1].pull()\n\n end = time.perf_counter()\n \n end_time = ts_now() \n \n \n print(f'Pull() finished in {round(end -start, 2)} second(s) \\\n for job {idx}')\n \n time_df = time_df.append({'START': start_time, \n 'END': end_time, \n 'DURATION': end -start, \n 'JOB_TYPE': 'pull', \n 'JOB_ID': idx}, ignore_index = True)\n \n start_time = ts_now() \n\n start = time.perf_counter()\n X_train = train_dat[['CREDIT_BALANCE', 'MORTGAGE_AMOUNT', 'BANK_FUNDS', \n 'NUM_DEPENDENTS', 'INCOME', 'CREDIT_CARD_LIMITS']]\n y_train = train_dat[['BUY_INSURANCE']]\n\n #clf = MLPClassifier(random_state=1, max_iter=500)\n #clf = LogisticRegression(random_state=0)\n\n clf = train_helper(X_train, y_train)\n end = time.perf_counter()\n end_time = ts_now() \n\n print(f'Training finished in {round(end -start, 2)} second(s) \\\n for job {idx}')\n time_df = time_df.append({'START': start_time, \n 'END': end_time, \n 'DURATION': end -start, \n 'JOB_TYPE': 'train', \n 'JOB_ID': idx}, ignore_index = True)\n\n\n start_time = ts_now() \n\n start = time.perf_counter()\n X_test = test_dat[['CREDIT_BALANCE', 'MORTGAGE_AMOUNT', 'BANK_FUNDS', \n 'NUM_DEPENDENTS', 'INCOME', 'CREDIT_CARD_LIMITS']]\n y_test = test_dat[['BUY_INSURANCE']]\n \n \n auc = roc_auc_score(y_test, clf.predict_proba(X_test)[:, 1]) \n\n end_time = ts_now() \n\n end = time.perf_counter()\n print(f'Scoring and metric finished in {round(end -start, 2)} second(s) \\\n for job {idx}')\n time_df = time_df.append({'START': start_time, \n 'END': end_time, \n 'DURATION': end -start, \n 'JOB_TYPE': 'score', \n 'JOB_ID': idx}, ignore_index = True)\n\n\n try:\n oml.drop(table = 'RECORD_DF_' + str(idx))\n except:\n pass\n \n _ = oml.create(time_df, table = 'RECORD_DF_' + str(idx))\n \n \n return auc\n","user":"JIE","dateUpdated":"2021-07-29T18:06:16+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[]},"interrupted":false,"jobName":"paragraph_1628000330915_1874251753","id":"20210803-141850_646594765","dateCreated":"2021-04-23T14:39:18+0000","dateStarted":"2021-07-29T18:06:17+0000","dateFinished":"2021-07-29T18:06:17+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:72"},{"title":"Parallel Run","text":"%python\r\n\r\nres = oml.index_apply(times=10, func=build_open_src, oml_connect=True, parallel =8, pairs = pairs, graphics = False, train_helper = train_rf)\r\n \r\nindex_df = combine_plot('RECORD_DF', 10) \r\n","user":"JIE","dateUpdated":"2021-07-29T17:57:09+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"text","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"Pull() finished in 0.59 second(s) for job 2\nPull() finished in 0.61 second(s) for job 3\nPull() finished in 0.66 second(s) for job 1\nPull() finished in 0.65 second(s) for job 4\nTraining finished in 2.31 second(s) for job 4\nTraining finished in 2.51 second(s) for job 3\nTraining finished in 2.52 second(s) for job 1\nTraining finished in 2.59 second(s) for job 2\nScoring and metric finished in 0.13 second(s) for job 4\nScoring and metric finished in 0.14 second(s) for job 3\nScoring and metric finished in 0.13 second(s) for job 1\nScoring and metric finished in 0.11 second(s) for job 2\nPull() finished in 0.53 second(s) for job 7Pull() finished in 0.54 second(s) for job 6\n\nPull() finished in 0.54 second(s) for job 8\nPull() finished in 0.58 second(s) for job 5\nTraining finished in 2.33 second(s) for job 5\nTraining finished in 2.41 second(s) for job 6\nTraining finished in 2.46 second(s) for job 7\nScoring and metric finished in 0.1 second(s) for job 5\nTraining finished in 2.49 second(s) for job 8\nScoring and metric finished in 0.12 second(s) for job 6\nScoring and metric finished in 0.11 second(s) for job 7\nScoring and metric finished in 0.1 second(s) for job 8\nPull() finished in 0.26 second(s) for job 9\nPull() finished in 0.29 second(s) for job 10\nTraining finished in 2.08 second(s) for job 9\nTraining finished in 1.97 second(s) for job 10\nScoring and metric finished in 0.07 second(s) for job 9\nScoring and metric finished in 0.07 second(s) for job 10\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_494686193","id":"20210803-141850_637659642","dateCreated":"2021-05-05T20:23:35+0000","dateStarted":"2021-07-29T17:57:10+0000","dateFinished":"2021-07-29T17:57:22+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:73"},{"title":"Serial Run","text":"%python\n\nfor i in range(1, 11):\n build_open_src(i, pairs, train_helper = train_rf)\nseries_df = combine_plot('RECORD_DF', 10) ","user":"JIE","dateUpdated":"2021-07-28T18:43:10+0000","config":{"colWidth":6,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"TEXT","data":"Pull() finished in 3.61 second(s) for job 1\nTraining finished in 17.23 second(s) for job 1\nScoring and metric finished in 0.37 second(s) for job 1\nPull() finished in 3.65 second(s) for job 2\nTraining finished in 17.46 second(s) for job 2\nScoring and metric finished in 0.35 second(s) for job 2\nPull() finished in 3.55 second(s) for job 3\nTraining finished in 17.18 second(s) for job 3\nScoring and metric finished in 0.34 second(s) for job 3\nPull() finished in 3.69 second(s) for job 4\nTraining finished in 17.11 second(s) for job 4\nScoring and metric finished in 0.35 second(s) for job 4\nPull() finished in 3.7 second(s) for job 5\nTraining finished in 16.84 second(s) for job 5\nScoring and metric finished in 0.37 second(s) for job 5\nPull() finished in 3.83 second(s) for job 6\nTraining finished in 16.88 second(s) for job 6\nScoring and metric finished in 0.33 second(s) for job 6\nPull() finished in 3.69 second(s) for job 7\nTraining finished in 16.98 second(s) for job 7\nScoring and metric finished in 0.33 second(s) for job 7\nPull() finished in 3.53 second(s) for job 8\nTraining finished in 17.12 second(s) for job 8\nScoring and metric finished in 0.35 second(s) for job 8\nPull() finished in 3.6 second(s) for job 9\nTraining finished in 17.05 second(s) for job 9\nScoring and metric finished in 0.36 second(s) for job 9\nPull() finished in 3.8 second(s) for job 10\nTraining finished in 17.03 second(s) for job 10\nScoring and metric finished in 0.35 second(s) for job 10\n"}]},"interrupted":false,"jobName":"paragraph_1628000330915_-1866782463","id":"20210803-141850_867474787","dateCreated":"2021-07-01T18:16:08+0000","dateStarted":"2021-07-28T18:43:11+0000","dateFinished":"2021-07-28T18:46:45+0000","status":"FINISHED","progressUpdateIntervalMs":500,"commited":true,"$$hashKey":"object:74"},{"title":"Plot for comparison","text":"%python\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\ncolors = {'pull': 'green', 'train': 'orange', 'score': 'cyan'}\n\n\nfig, axs = plt.subplots(2, figsize=(15, 10))\n\njob_types = ['pull', 'train', 'score']\n\nmin_start = min(index_df['START'].values)\nmax_end = max(index_df['END'].values)\nmax_range = (max_end - min_start).item()/10**9\n\n\nmin_start = min(series_df['START'].values) \nmax_end = max(series_df['END'].values)\n\nmax_range = max(max_range, (max_end - min_start).item()/10**9)\n\n\nplt.style.use('seaborn-whitegrid')\n\nplot_sub(index_df, job_types, axs[0], max_range)\n\naxs[0].set_title('Paralleled Run',fontweight=\"bold\", size=20) # Title\nupper = 240\naxs[0].set_xlim([0, upper])\nmajor_ticks = np.arange(0, upper, 20)\naxs[0].set_xticks(major_ticks)\n\nplot_sub(series_df, job_types, axs[1], max_range)\n\naxs[1].set_title('Serial Run',fontweight=\"bold\", size=20) # Title\n#plt.ylabel('Job ID', fontsize=20)\n#plt.xlabel('Time (second)', fontsize=20)\naxs[1].set_xticks(major_ticks)\n\naxs[1].set_xlim([0, upper])\n#plt.rcParams[\"font.size\"] = \"10\"\nplt.show() ","user":"JIE","dateUpdated":"2021-07-27T19:25:34+0000","config":{"colWidth":12,"fontSize":9,"enabled":true,"results":{},"editorSetting":{"language":"sql","editOnDblClick":false},"editorMode":"ace/mode/undefined","title":true},"settings":{"params":{},"forms":{}},"results":{"code":"SUCCESS","msg":[{"type":"HTML","data":"
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