{ "cells": [ { "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "## Решение для хакатона ОЗОН\n", "\n", "2017, Александр Дьяконов" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Populating the interactive namespace from numpy and matplotlib\n" ] } ], "source": [ "# подгружаем все нужные пакеты\n", "import pandas as pd\n", "import numpy as np\n", "\n", "\n", "# для встроенных картинок\n", "%pylab inline\n", "# чуть покрасивше картинки:\n", "pd.set_option('display.mpl_style', 'default')\n", "figsize(12, 9)\n", "\n", "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "\n", "#plt.rcParams['figure.figsize'] = 10, 7.5\n", "#plt.rcParams['axes.grid'] = True\n", "pd.set_option('display.max_columns', None)\n", "import matplotlib.pyplot as plt\n", "\n", "import matplotlib as mpl\n", "mpl.rcParams['font.family'] = 'Ubuntu'\n", "\n", "plt.rc('text', usetex=False)\n", "plt.rc('font', family='serif')\n", "plt.rc('font', weight='bold')\n", "plt.rc('xtick', labelsize=14) \n", "plt.rc('ytick', labelsize=14)\n", "\n", "# чтобы был русский шрифт\n", "from matplotlib import rc\n", " \n", "font = {'family': 'Droid Sans',\n", " 'weight': 'normal'}\n", "rc('font', **font)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# data = pd.read_excel('Training Part.xlsx')\n", "# day1 = pd.read_excel('day1.xlsx')\n", "# day2 = pd.read_excel('day2.xlsx')" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [], "source": [ "data = pd.read_csv('data.csv')\n", "day1 = pd.read_csv('day1.csv')\n", "day2 = pd.read_csv('day2.csv')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(390000, 197) (130000, 197) (132016, 197)\n" ] } ], "source": [ "print (data.shape, day1.shape, day2.shape)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " ID NetSales gender ActivityIndex Alcohol AverageFriendsRegMonthDelta \\\n", "0 1 0.0 F - 0.0 92 \n", "1 7 0.0 F - 0.0 - \n", "2 13 0.0 F - 0.0 96 \n", "3 19 180.0 M 4.58 0.0 89 \n", "4 25 4876.4 F 5.74 0.0 97 \n", "\n", " CanSeeAllPosts CanSeeAllPosts_CanPost EducationType EducationType_VK \\\n", "0 - - 12 - \n", "1 - - - - \n", "2 - - 12 - \n", "3 0 1 0 0 \n", "4 0 1 - - \n", "\n", " FriendsAverageDeletedAccounts FriendsAverageHasHighSchools \\\n", "0 0.06667 0.33333 \n", "1 0 0.33333 \n", "2 0.11579 0.45263 \n", "3 0.02691 0.72197 \n", "4 0.01754 0.625 \n", "\n", " FriendsAverageHasJobs FriendsPerDay HasPhone HasSkype HasTwitter \\\n", "0 0.06667 0.01768 0.0 0.0 0.0 \n", "1 0.22222 - 0.0 0.0 0.0 \n", "2 0.06316 0.03699 0.0 0.0 0.0 \n", "3 0.10762 0.07254 0.0 0.0 0.0 \n", "4 0.33114 0.15117 0.0 0.0 0.0 \n", "\n", " LastActivity LifeTime MaxRegDate MinRegDate \\\n", "0 113 2623 2012-10-19 00:00:00 2008-01-20 00:00:00 \n", "1 79 - 2008-06-22 00:00:00 2008-06-22 00:00:00 \n", "2 145 2514 2008-02-19 00:00:00 2008-02-19 00:00:00 \n", "3 3 2578 2008-06-26 00:00:00 2008-06-09 00:00:00 \n", "4 0 2785 2007-11-29 00:00:00 2007-11-29 00:00:00 \n", "\n", " MobileUsageAll MobileUsageAndroid MobileUsageIPad MobileUsageIphone \\\n", "0 - - - - \n", "1 - - - - \n", "2 - - - - \n", "3 0.93583 0 0.65714 0.10857 \n", "4 0.51657 0 0 0.9893 \n", "\n", " MobileUsageWinPhone MonthsFromMaxRegDate MonthsFromMinRegDate \\\n", "0 - 51 108 \n", "1 - 103 103 \n", "2 - 107 107 \n", "3 0 103 103 \n", "4 0 110 110 \n", "\n", " NumberOfAccounts NumberOfAccountsMOIMIR NumberOfAccountsODKL \\\n", "0 2.0 0.0 2.0 \n", "1 1.0 1.0 0.0 \n", "2 1.0 0.0 1.0 \n", "3 2.0 1.0 0.0 \n", "4 1.0 0.0 0.0 \n", "\n", " NumberOfAccountsVK NumberOfAdvancedSchools NumberOfChilds \\\n", "0 0.0 0.0 0 \n", "1 0.0 0.0 0 \n", "2 0.0 0.0 0 \n", "3 1.0 2.0 0 \n", "4 1.0 0.0 0 \n", "\n", " NumberOfChilds_VK NumberOfCompanies NumberOfDeletedAccounts \\\n", "0 - 0.0 0.0 \n", "1 - 0.0 0.0 \n", "2 - 0.0 1.0 \n", "3 0 0.0 0.0 \n", "4 0 1.0 0.0 \n", "\n", " NumberOfDeletedAccounts_VK NumberOfEntrance NumberOfFollowers \\\n", "0 - - - \n", "1 - - - \n", "2 - - - \n", "3 0 123 105 \n", "4 0 253 105 \n", "\n", " NumberOfFriendsMax NumberOfFriendsMax_VK NumberOfFriendsMin \\\n", "0 14 - 1 \n", "1 8 - 8 \n", "2 93 - 93 \n", "3 187 187 16 \n", "4 421 421 421 \n", "\n", " NumberOfFriendsSum NumberOfGroupsMax NumberOfGroupsSum_OK \\\n", "0 15 - - \n", "1 8 - - \n", "2 93 3 3 \n", "3 203 28 - \n", "4 421 - - \n", "\n", " NumberOfHighSchools NumberOfNotesMax NumberOfPhotosMax \\\n", "0 1.0 0 1 \n", "1 0.0 - 4 \n", "2 1.0 7 11 \n", "3 1.0 - 96 \n", "4 0.0 - 128 \n", "\n", " NumberOfPhotosMin_VK NumberOfPrivateAccounts NumberOfPrivateAccounts_OK \\\n", "0 - 0.0 0 \n", "1 - 1.0 - \n", "2 - 0.0 0 \n", "3 96 0.0 - \n", "4 128 0.0 - \n", "\n", " NumberOfRelatives NumberOfRelatives_OK NumberOfSchools \\\n", "0 4.0 4 1.0 \n", "1 0.0 - 0.0 \n", "2 0.0 0 1.0 \n", "3 0.0 - 2.0 \n", "4 0.0 - 0.0 \n", "\n", " NumberOfSubscriptions NumberOfVideos Relation SaScore1 SaScore2 \\\n", "0 - - 0.0 -3.82756 -1.67380 \n", "1 - - 0.0 -4.06040 -1.92671 \n", "2 - - 0.0 -4.00498 -1.88295 \n", "3 31 246 0.0 -3.97826 -2.78780 \n", "4 59 22 0.0 -4.45843 -3.21992 \n", "\n", " SaScore5 SaScore6 SaScore7 SaScoreFraud SaScoreSocial Smoking \\\n", "0 -5.15525 -6.52538 113.0 -4.14635 -4.86583 0.0 \n", "1 -4.93723 -6.52939 110.0 -3.98769 -5.21042 0.0 \n", "2 -5.82966 -7.60862 108.0 -4.59382 -4.86583 0.0 \n", "3 -5.45857 -7.31933 91.0 -4.87099 -4.90845 0.0 \n", "4 -5.08907 -6.78496 99.0 -4.95631 -5.04582 0.0 \n", "\n", " UseScreenName Worldviews YearsSinceMinRegDate YearsSinceMinRegDate_OK \\\n", "0 0.0 0.0 9.0197 9.0197 \n", "1 0.0 0.0 8.59808 - \n", "2 0.0 0.0 8.93898 8.93898 \n", "3 1.0 0.0 8.63466 - \n", "4 1.0 0.0 9.16308 - \n", "\n", " YearsSinceMinRegDate_VK NumberOfAccountsFB Interest_1 Interest_2 \\\n", "0 - NaN - - \n", "1 - NaN - - \n", "2 - 1.0 - - \n", "3 8.58786 1.0 0 0 \n", "4 9.16308 1.0 0 1 \n", "\n", " Interest_3 Interest_4 Interest_5 Interest_6 Interest_7 Interest_8 \\\n", "0 - - - - - - \n", "1 - - - - - - \n", "2 - - - - - - \n", "3 0 4 0 6 1 0 \n", "4 1 0 2 0 4 7 \n", "\n", " Interest_9 Interest_10 Interest_11 Interest_12 Interest_13 Interest_14 \\\n", "0 - - - - - - \n", "1 - - - - - - \n", "2 - - - - - - \n", "3 8 5 8 0 7 0 \n", "4 8 0 2 8 0 5 \n", "\n", " Interest_15 Interest_16 Interest_17 Interest_18 Interest_19 Interest_20 \\\n", "0 - - - - - - \n", "1 - - - - - - \n", "2 - - - - - - \n", "3 6 0 10 4 0 0 \n", "4 0 0 0 1 0 0 \n", "\n", " Interest_21 Interest_22 Interest_23 Interest_24 Interest_25 \\\n", "0 - - - - - \n", "1 - - - - - \n", "2 - - - - - \n", "3 0 0 0 0 0 \n", "4 0 0 0 0 0 \n", "\n", " TD_acquaint_communic TD_acquaintances TD_active_rest TD_ad \\\n", "0 NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 0.00000 0.0 0.026316 0.00000 \n", "4 0.00641 0.0 0.000000 0.00641 \n", "\n", " TD_animals TD_anime_hentai TD_architecture TD_art_design \\\n", "0 NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 0.008772 0.0 0.0 0.035088 \n", "4 0.000000 0.0 0.0 0.121795 \n", "\n", " TD_beautiful_girls TD_beauty TD_books TD_business TD_cars \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.00000 0.035088 0.008772 0.008772 \n", "4 0.0 0.00641 0.000000 0.006410 0.000000 \n", "\n", " TD_cartoons TD_caucasian TD_celebrities TD_children TD_cognitive \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.0 0.00000 0.0 0.035088 \n", "4 0.0 0.0 0.00641 0.0 0.000000 \n", "\n", " TD_companies TD_computers TD_cookery TD_design TD_design_renovation \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.0 0.00000 0.000000 0.0 \n", "4 0.0 0.0 0.00641 0.038462 0.0 \n", "\n", " TD_diets TD_do_yourself TD_electronics_electrappliances \\\n", "0 NaN NaN NaN \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 0.0 0.000000 0.0 \n", "4 0.0 0.019231 0.0 \n", "\n", " TD_entertainment TD_family_home TD_fashion TD_finance TD_fitness \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.122807 0.000000 0.00000 0.008772 0.00000 \n", "4 0.025641 0.083333 0.00641 0.000000 0.00641 \n", "\n", " TD_football TD_foreign_lang TD_gadgets TD_games TD_geopolitics_economy \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.026316 0.00000 0.0 0.0 \n", "4 0.0 0.000000 0.00641 0.0 0.0 \n", "\n", " TD_gif TD_goods_services TD_hobbies TD_horoscope TD_horror TD_humour \\\n", "0 NaN NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN NaN \n", "3 0.0 0.043860 0.035088 0.0 0.0 0.008772 \n", "4 0.0 0.121795 0.006410 0.0 0.0 0.012821 \n", "\n", " TD_images TD_insurance TD_interior TD_kazakhstan TD_landscape_design \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.026316 0.0 0.000000 0.0 0.0 \n", "4 0.038462 0.0 0.019231 0.0 0.0 \n", "\n", " TD_literature_poetry TD_mass_media TD_mass_media_ad_PR \\\n", "0 NaN NaN NaN \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 0.052632 0.00000 0.000000 \n", "4 0.000000 0.00641 0.019231 \n", "\n", " TD_men_communities TD_mobile_internet TD_motivation TD_moto TD_movies \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.008772 0.0 0.00000 0.0 0.008772 \n", "4 0.006410 0.0 0.00641 0.0 0.012821 \n", "\n", " TD_music TD_names TD_nature TD_nature_and_travel TD_nostalgia \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.087719 0.0 0.0 0.017544 0.0 \n", "4 0.000000 0.0 0.0 0.000000 0.0 \n", "\n", " TD_other_services TD_parents_communities TD_philosophy_esoterics \\\n", "0 NaN NaN NaN \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 0.000000 0.0 0.0 \n", "4 0.032051 0.0 0.0 \n", "\n", " TD_photo TD_poetry TD_politics TD_professions TD_proposed_news \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.008772 0.017544 0.0 0.0 0.00000 \n", "4 0.025641 0.000000 0.0 0.0 0.00641 \n", "\n", " TD_real_estate TD_regional_communities TD_relations TD_religion \\\n", "0 NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 0.00000 0.026316 0.00000 0.0 \n", "4 0.00641 0.032051 0.00641 0.0 \n", "\n", " TD_rest TD_russia TD_science TD_science_education TD_shops \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.061404 0.008772 0.008772 0.070175 0.043860 \n", "4 0.025641 0.012821 0.000000 0.000000 0.083333 \n", "\n", " TD_slimming TD_society TD_soft TD_softporno_porno TD_sport_and_health \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.00000 0.0 0.00000 0.0 0.043860 \n", "4 0.00641 0.0 0.00641 0.0 0.019231 \n", "\n", " TD_sport_diet TD_sport_other TD_start_ups TD_tech_IT TD_technologies \\\n", "0 NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.017544 0.017544 0.0 0.000000 0.0 \n", "4 0.006410 0.000000 0.0 0.012821 0.0 \n", "\n", " TD_thoughts_ideas TD_tourism TD_travel TD_TV TD_ukraine TD_video \\\n", "0 NaN NaN NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN NaN \n", "3 0.0 0.0 0.008772 0.026316 0.0 0.000000 \n", "4 0.0 0.0 0.000000 0.000000 0.0 0.012821 \n", "\n", " TD_way_of_life TD_wedding_communities TD_women_communities TD_workout \\\n", "0 NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 0.0 0.000000 0.000000 0.008772 \n", "4 0.0 0.076923 0.012821 0.000000 \n", "\n", " TD_youth_communities TD_sum animal_owner \n", "0 NaN NaN NaN \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 0.026316 114.0 0.0 \n", "4 0.019231 156.0 1.0 " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ 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2390016NaNF-0.087--12-0.031250.171880.031250.017740.00.00.02110032012-07-18 00:00:002008-03-26 00:00:00-----541063.01.02.00.00.00.0-0.00.0---44-161--2.0132-0.000.001.0--0.0-3.57804-1.89699-4.78375-6.30990124.0-3.51037-4.465520.00.00.08.839844.80161-NaN-------------------------NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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" ], "text/plain": [ " ID NetSales gender ActivityIndex Alcohol AverageFriendsRegMonthDelta \\\n", "0 390004 NaN F NaN NaN NaN \n", "1 390010 NaN NaN 4.5 0.0 60 \n", "2 390016 NaN F - 0.0 87 \n", "3 390022 NaN F 5.79 0.0 85 \n", "4 390028 NaN F - 0.0 - \n", "\n", " CanSeeAllPosts CanSeeAllPosts_CanPost EducationType EducationType_VK \\\n", "0 NaN NaN NaN NaN \n", "1 1 1 - - \n", "2 - - 12 - \n", "3 0 1 0 0 \n", "4 - - 13 - \n", "\n", " FriendsAverageDeletedAccounts FriendsAverageHasHighSchools \\\n", "0 NaN NaN \n", "1 0.04138 0.18506 \n", "2 0.03125 0.17188 \n", "3 0.02874 0.56897 \n", "4 0 0.47059 \n", "\n", " FriendsAverageHasJobs FriendsPerDay HasPhone HasSkype HasTwitter \\\n", "0 NaN NaN NaN NaN NaN \n", "1 0.07356 0.14374 1.0 0.0 0.0 \n", "2 0.03125 0.01774 0.0 0.0 0.0 \n", "3 0.21839 0.04461 0.0 0.0 0.0 \n", "4 0.11765 - 0.0 0.0 0.0 \n", "\n", " LastActivity LifeTime MaxRegDate MinRegDate \\\n", "0 NaN NaN NaN NaN \n", "1 1 2261 2014-03-12 00:00:00 2009-06-30 00:00:00 \n", "2 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IDNet SalesgenderActivityIndexAlcoholAverageFriendsRegMonthDeltaCanSeeAllPostsCanSeeAllPosts_CanPostEducationTypeEducationType_VKFriendsAverageDeletedAccountsFriendsAverageHasHighSchoolsFriendsAverageHasJobsFriendsPerDayHasPhoneHasSkypeHasTwitterLastActivityLifeTimeMaxRegDateMinRegDateMobileUsageAllMobileUsageAndroidMobileUsageIPadMobileUsageIphoneMobileUsageWinPhoneMonthsFromMaxRegDateMonthsFromMinRegDateNumberOfAccountsNumberOfAccountsMOIMIRNumberOfAccountsODKLNumberOfAccountsVKNumberOfAdvancedSchoolsNumberOfChildsNumberOfChilds_VKNumberOfCompaniesNumberOfDeletedAccountsNumberOfDeletedAccounts_VKNumberOfEntranceNumberOfFollowersNumberOfFriendsMaxNumberOfFriendsMax_VKNumberOfFriendsMinNumberOfFriendsSumNumberOfGroupsMaxNumberOfGroupsSum_OKNumberOfHighSchoolsNumberOfNotesMaxNumberOfPhotosMaxNumberOfPhotosMin_VKNumberOfPrivateAccountsNumberOfPrivateAccounts_OKNumberOfRelativesNumberOfRelatives_OKNumberOfSchoolsNumberOfSubscriptionsNumberOfVideosRelationSaScore1SaScore2SaScore5SaScore6SaScore7SaScoreFraudSaScoreSocialSmokingUseScreenNameWorldviewsYearsSinceMinRegDateYearsSinceMinRegDate_OKYearsSinceMinRegDate_VKNumberOfAccountsFBInterest_1Interest_2Interest_3Interest_4Interest_5Interest_6Interest_7Interest_8Interest_9Interest_10Interest_11Interest_12Interest_13Interest_14Interest_15Interest_16Interest_17Interest_18Interest_19Interest_20Interest_21Interest_22Interest_23Interest_24Interest_25TD_acquaint_communicTD_acquaintancesTD_active_restTD_adTD_animalsTD_anime_hentaiTD_architectureTD_art_designTD_beautiful_girlsTD_beautyTD_booksTD_businessTD_carsTD_cartoonsTD_caucasianTD_celebritiesTD_childrenTD_cognitiveTD_companiesTD_computersTD_cookeryTD_designTD_design_renovationTD_dietsTD_do_yourselfTD_electronics_electrappliancesTD_entertainmentTD_family_homeTD_fashionTD_financeTD_fitnessTD_footballTD_foreign_langTD_gadgetsTD_gamesTD_geopolitics_economyTD_gifTD_goods_servicesTD_hobbiesTD_horoscopeTD_horrorTD_humourTD_imagesTD_insuranceTD_interiorTD_kazakhstanTD_landscape_designTD_literature_poetryTD_mass_mediaTD_mass_media_ad_PRTD_men_communitiesTD_mobile_internetTD_motivationTD_motoTD_moviesTD_musicTD_namesTD_natureTD_nature_and_travelTD_nostalgiaTD_other_servicesTD_parents_communitiesTD_philosophy_esotericsTD_photoTD_poetryTD_politicsTD_professionsTD_proposed_newsTD_real_estateTD_regional_communitiesTD_relationsTD_religionTD_restTD_russiaTD_scienceTD_science_educationTD_shopsTD_slimmingTD_societyTD_softTD_softporno_pornoTD_sport_and_healthTD_sport_dietTD_sport_otherTD_start_upsTD_tech_ITTD_technologiesTD_thoughts_ideasTD_tourismTD_travelTD_TVTD_ukraineTD_videoTD_way_of_lifeTD_wedding_communitiesTD_women_communitiesTD_workoutTD_youth_communitiesTD_sumanimal_owner
0520001NaNM0.90.078120000.240.120.003380.00.00.0114782011-08-23 00:00:002008-12-25 00:00:000.75100065972.01.00.01.00.00.000.00.00311855239-1.0-410.0-0.0-1.0687.0-4.07950-2.42172-4.79584-6.03038121.0-3.95212-4.193400.01.00.08.08853-5.429521.0000000000000000001000000000.0000000.00.00.0000000.00.00.00.1333330.00.00.0000000.1333330.00.00.00.0000000.00.00.0000000.00.0000000.0000000.00.00.00.00.0000000.00.0000000.00.00.00.00.00.000.00.00.0000000.0000000.0000000.00.0000000.1333330.00.0000000.00.00.0000000.00.0000000.0000000.00.1333330.00.0000000.0000000.00.00.0000.00.0000000.00.0666670.00.00.0000000.00.0000000.00.0000000.00.00.0000000.0000000.00.0666670.0000000.00.0000000.00.00.00.00.00.00.00.0666670.00.00.0000.0000000.00.00.0666670.00.0000000.00.215.00.0
1520007NaNM-2.09212000.090530.395060.160490.338460.00.00.03922882012-01-10 00:00:002009-03-02 00:00:000000060943.01.01.01.00.00.001.00.00-620922323419161.0101440.003.032.0-67.0-3.57355-1.58798-4.35452-5.16231132.0-4.28645-4.618782.00.01.07.904217.904215.043921.0-------------------------NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2520013NaNF-0.080----0.033560.442950.154360.092440.00.00.0024952014-05-14 00:00:002008-08-19 00:00:00-----321013.01.02.00.00.00.0-0.00.0---70-4418128280.048238-2.0113.0150.0--0.0-3.98220-1.75361-5.49793-6.42880143.0-4.40719-4.611410.00.00.08.440498.36627-1.0-------------------------NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3520019NaNF2.990.07901000.078260.582610.104350.028850.00.00.0019762010-04-04 00:00:002010-04-04 00:00:000.9506200.29870.68831081812.01.00.01.00.00.000.00.00541835757057--1.0-10100.0-0.0-0.01720.0-3.97585-2.85935-5.49487-7.18308106.0-4.57233-4.286060.01.00.06.81516-6.814521.067005040700080008000000000.0481930.00.00.0120480.00.00.00.0481930.00.00.0240960.0000000.00.00.00.0120480.00.00.0120480.00.0361450.0120480.00.00.00.00.0843370.00.0240960.00.00.00.00.00.000.00.00.0843370.0120480.0120480.00.0722890.0240960.00.0120480.00.00.0240960.00.0240960.0361450.00.0000000.00.0240960.0361450.00.00.0000.00.0120480.00.0120480.00.00.0120480.00.0481930.00.0722890.00.00.0120480.0240960.00.0000000.0602410.00.0120480.00.00.00.00.00.00.00.0000000.00.00.0000.0240960.00.00.0000000.00.0361450.00.083.00.0
4520025NaNM2.360.06412--00.368420.210530.015760.00.00.0010792012-07-09 00:00:002008-09-11 00:00:000.173911000541002.00.01.01.01.00.000.00.0015-1717017--0.00--0.000.002.01-7.0-3.77161-2.84637-4.91313-6.43954120.0-4.10089-4.607500.00.00.08.376648.376644.548721.000000000000000000000000000.0000000.00.00.0000000.00.00.00.0000000.00.00.0000000.0000000.00.00.00.0000000.00.00.0000000.00.0000000.0000000.00.00.00.00.2500000.00.0000000.00.00.00.00.00.250.00.00.1250000.0000000.0000000.00.0000000.0000000.00.0000000.00.00.0000000.00.0000000.0000000.00.0000000.00.0000000.0000000.00.00.1250.00.0000000.00.0000000.00.00.0000000.00.0000000.00.0000000.00.00.0000000.0000000.00.0000000.1250000.00.0000000.00.00.00.00.00.00.00.0000000.00.00.1250.0000000.00.00.0000000.00.0000000.00.08.00.0
\n", "
" ], "text/plain": [ " ID Net Sales gender ActivityIndex Alcohol \\\n", "0 520001 NaN M 0.9 0.0 \n", "1 520007 NaN M - 2.0 \n", "2 520013 NaN F - 0.0 \n", "3 520019 NaN F 2.99 0.0 \n", "4 520025 NaN M 2.36 0.0 \n", "\n", " AverageFriendsRegMonthDelta CanSeeAllPosts CanSeeAllPosts_CanPost \\\n", "0 78 1 2 \n", "1 92 1 2 \n", "2 80 - - \n", "3 79 0 1 \n", "4 64 1 2 \n", "\n", " EducationType EducationType_VK FriendsAverageDeletedAccounts \\\n", "0 0 0 0 \n", "1 0 0 0.09053 \n", "2 - - 0.03356 \n", "3 0 0 0.07826 \n", "4 - - 0 \n", "\n", " FriendsAverageHasHighSchools FriendsAverageHasJobs FriendsPerDay HasPhone \\\n", "0 0.24 0.12 0.00338 0.0 \n", "1 0.39506 0.16049 0.33846 0.0 \n", "2 0.44295 0.15436 0.09244 0.0 \n", "3 0.58261 0.10435 0.02885 0.0 \n", "4 0.36842 0.21053 0.01576 0.0 \n", "\n", " HasSkype HasTwitter LastActivity LifeTime MaxRegDate \\\n", "0 0.0 0.0 1 1478 2011-08-23 00:00:00 \n", "1 0.0 0.0 39 2288 2012-01-10 00:00:00 \n", "2 0.0 0.0 0 2495 2014-05-14 00:00:00 \n", "3 0.0 0.0 0 1976 2010-04-04 00:00:00 \n", "4 0.0 0.0 0 1079 2012-07-09 00:00:00 \n", "\n", " MinRegDate MobileUsageAll MobileUsageAndroid MobileUsageIPad \\\n", "0 2008-12-25 00:00:00 0.75 1 0 \n", "1 2009-03-02 00:00:00 0 0 0 \n", "2 2008-08-19 00:00:00 - - - \n", "3 2010-04-04 00:00:00 0.95062 0 0.2987 \n", "4 2008-09-11 00:00:00 0.17391 1 0 \n", "\n", " MobileUsageIphone MobileUsageWinPhone MonthsFromMaxRegDate \\\n", "0 0 0 65 \n", "1 0 0 60 \n", "2 - - 32 \n", "3 0.68831 0 81 \n", "4 0 0 54 \n", "\n", " MonthsFromMinRegDate NumberOfAccounts NumberOfAccountsMOIMIR \\\n", "0 97 2.0 1.0 \n", "1 94 3.0 1.0 \n", "2 101 3.0 1.0 \n", "3 81 2.0 1.0 \n", "4 100 2.0 0.0 \n", "\n", " NumberOfAccountsODKL NumberOfAccountsVK NumberOfAdvancedSchools \\\n", "0 0.0 1.0 0.0 \n", "1 1.0 1.0 0.0 \n", "2 2.0 0.0 0.0 \n", "3 0.0 1.0 0.0 \n", "4 1.0 1.0 1.0 \n", "\n", " NumberOfChilds NumberOfChilds_VK NumberOfCompanies \\\n", "0 0.0 0 0.0 \n", "1 0.0 0 1.0 \n", "2 0.0 - 0.0 \n", "3 0.0 0 0.0 \n", "4 0.0 0 0.0 \n", "\n", " NumberOfDeletedAccounts NumberOfDeletedAccounts_VK NumberOfEntrance \\\n", "0 0.0 0 3 \n", "1 0.0 0 - \n", "2 0.0 - - \n", "3 0.0 0 54 \n", "4 0.0 0 15 \n", "\n", " NumberOfFollowers NumberOfFriendsMax NumberOfFriendsMax_VK \\\n", "0 1 18 5 \n", "1 6 209 22 \n", "2 - 70 - \n", "3 183 57 57 \n", "4 - 17 17 \n", "\n", " NumberOfFriendsMin NumberOfFriendsSum NumberOfGroupsMax \\\n", "0 5 23 9 \n", "1 3 234 19 \n", "2 44 181 28 \n", "3 0 57 - \n", "4 0 17 - \n", "\n", " NumberOfGroupsSum_OK NumberOfHighSchools NumberOfNotesMax \\\n", "0 - 1.0 - \n", "1 16 1.0 10 \n", "2 28 0.0 48 \n", "3 - 1.0 - \n", "4 - 0.0 0 \n", "\n", " NumberOfPhotosMax NumberOfPhotosMin_VK NumberOfPrivateAccounts \\\n", "0 4 1 0.0 \n", "1 14 4 0.0 \n", "2 238 - 2.0 \n", "3 10 10 0.0 \n", "4 - - 0.0 \n", "\n", " NumberOfPrivateAccounts_OK NumberOfRelatives NumberOfRelatives_OK \\\n", "0 - 0.0 - \n", "1 0 3.0 3 \n", "2 1 13.0 15 \n", "3 - 0.0 - \n", "4 0 0.0 0 \n", "\n", " NumberOfSchools NumberOfSubscriptions NumberOfVideos Relation SaScore1 \\\n", "0 1.0 6 8 7.0 -4.07950 \n", "1 2.0 - 6 7.0 -3.57355 \n", "2 0.0 - - 0.0 -3.98220 \n", "3 0.0 17 2 0.0 -3.97585 \n", "4 2.0 1 - 7.0 -3.77161 \n", "\n", " SaScore2 SaScore5 SaScore6 SaScore7 SaScoreFraud SaScoreSocial \\\n", "0 -2.42172 -4.79584 -6.03038 121.0 -3.95212 -4.19340 \n", "1 -1.58798 -4.35452 -5.16231 132.0 -4.28645 -4.61878 \n", "2 -1.75361 -5.49793 -6.42880 143.0 -4.40719 -4.61141 \n", "3 -2.85935 -5.49487 -7.18308 106.0 -4.57233 -4.28606 \n", "4 -2.84637 -4.91313 -6.43954 120.0 -4.10089 -4.60750 \n", "\n", " Smoking UseScreenName Worldviews YearsSinceMinRegDate \\\n", "0 0.0 1.0 0.0 8.08853 \n", "1 2.0 0.0 1.0 7.90421 \n", "2 0.0 0.0 0.0 8.44049 \n", "3 0.0 1.0 0.0 6.81516 \n", "4 0.0 0.0 0.0 8.37664 \n", "\n", " YearsSinceMinRegDate_OK YearsSinceMinRegDate_VK NumberOfAccountsFB \\\n", "0 - 5.42952 1.0 \n", "1 7.90421 5.04392 1.0 \n", "2 8.36627 - 1.0 \n", "3 - 6.81452 1.0 \n", "4 8.37664 4.54872 1.0 \n", "\n", " Interest_1 Interest_2 Interest_3 Interest_4 Interest_5 Interest_6 \\\n", "0 0 0 0 0 0 0 \n", "1 - - - - - - \n", "2 - - - - - - \n", "3 6 7 0 0 5 0 \n", "4 0 0 0 0 0 0 \n", "\n", " Interest_7 Interest_8 Interest_9 Interest_10 Interest_11 Interest_12 \\\n", "0 0 0 0 0 0 0 \n", "1 - - - - - - \n", "2 - - - - - - \n", "3 4 0 7 0 0 0 \n", "4 0 0 0 0 0 0 \n", "\n", " Interest_13 Interest_14 Interest_15 Interest_16 Interest_17 Interest_18 \\\n", "0 0 0 0 0 0 10 \n", "1 - - - - - - \n", "2 - - - - - - \n", "3 8 0 0 0 8 0 \n", "4 0 0 0 0 0 0 \n", "\n", " Interest_19 Interest_20 Interest_21 Interest_22 Interest_23 Interest_24 \\\n", "0 0 0 0 0 0 0 \n", "1 - - - - - - \n", "2 - - - - - - \n", "3 0 0 0 0 0 0 \n", "4 0 0 0 0 0 0 \n", "\n", " Interest_25 TD_acquaint_communic TD_acquaintances TD_active_rest \\\n", "0 0 0.000000 0.0 0.0 \n", "1 - NaN NaN NaN \n", "2 - NaN NaN NaN \n", "3 0 0.048193 0.0 0.0 \n", "4 0 0.000000 0.0 0.0 \n", "\n", " TD_ad TD_animals TD_anime_hentai TD_architecture TD_art_design \\\n", "0 0.000000 0.0 0.0 0.0 0.133333 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.012048 0.0 0.0 0.0 0.048193 \n", "4 0.000000 0.0 0.0 0.0 0.000000 \n", "\n", " TD_beautiful_girls TD_beauty TD_books TD_business TD_cars TD_cartoons \\\n", "0 0.0 0.0 0.000000 0.133333 0.0 0.0 \n", "1 NaN NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN NaN \n", "3 0.0 0.0 0.024096 0.000000 0.0 0.0 \n", "4 0.0 0.0 0.000000 0.000000 0.0 0.0 \n", "\n", " TD_caucasian TD_celebrities TD_children TD_cognitive TD_companies \\\n", "0 0.0 0.000000 0.0 0.0 0.000000 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.012048 0.0 0.0 0.012048 \n", "4 0.0 0.000000 0.0 0.0 0.000000 \n", "\n", " TD_computers TD_cookery TD_design TD_design_renovation TD_diets \\\n", "0 0.0 0.000000 0.000000 0.0 0.0 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.036145 0.012048 0.0 0.0 \n", "4 0.0 0.000000 0.000000 0.0 0.0 \n", "\n", " TD_do_yourself TD_electronics_electrappliances TD_entertainment \\\n", "0 0.0 0.0 0.000000 \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 0.0 0.0 0.084337 \n", "4 0.0 0.0 0.250000 \n", "\n", " TD_family_home TD_fashion TD_finance TD_fitness TD_football \\\n", "0 0.0 0.000000 0.0 0.0 0.0 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.024096 0.0 0.0 0.0 \n", "4 0.0 0.000000 0.0 0.0 0.0 \n", "\n", " TD_foreign_lang TD_gadgets TD_games TD_geopolitics_economy TD_gif \\\n", "0 0.0 0.0 0.00 0.0 0.0 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.0 0.00 0.0 0.0 \n", "4 0.0 0.0 0.25 0.0 0.0 \n", "\n", " TD_goods_services TD_hobbies TD_horoscope TD_horror TD_humour \\\n", "0 0.000000 0.000000 0.000000 0.0 0.000000 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.084337 0.012048 0.012048 0.0 0.072289 \n", "4 0.125000 0.000000 0.000000 0.0 0.000000 \n", "\n", " TD_images TD_insurance TD_interior TD_kazakhstan TD_landscape_design \\\n", "0 0.133333 0.0 0.000000 0.0 0.0 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.024096 0.0 0.012048 0.0 0.0 \n", "4 0.000000 0.0 0.000000 0.0 0.0 \n", "\n", " TD_literature_poetry TD_mass_media TD_mass_media_ad_PR \\\n", "0 0.000000 0.0 0.000000 \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 0.024096 0.0 0.024096 \n", "4 0.000000 0.0 0.000000 \n", "\n", " TD_men_communities TD_mobile_internet TD_motivation TD_moto TD_movies \\\n", "0 0.000000 0.0 0.133333 0.0 0.000000 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.036145 0.0 0.000000 0.0 0.024096 \n", "4 0.000000 0.0 0.000000 0.0 0.000000 \n", "\n", " TD_music TD_names TD_nature TD_nature_and_travel TD_nostalgia \\\n", "0 0.000000 0.0 0.0 0.000 0.0 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.036145 0.0 0.0 0.000 0.0 \n", "4 0.000000 0.0 0.0 0.125 0.0 \n", "\n", " TD_other_services TD_parents_communities TD_philosophy_esoterics \\\n", "0 0.000000 0.0 0.066667 \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 0.012048 0.0 0.012048 \n", "4 0.000000 0.0 0.000000 \n", "\n", " TD_photo TD_poetry TD_politics TD_professions TD_proposed_news \\\n", "0 0.0 0.0 0.000000 0.0 0.000000 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.0 0.012048 0.0 0.048193 \n", "4 0.0 0.0 0.000000 0.0 0.000000 \n", "\n", " TD_real_estate TD_regional_communities TD_relations TD_religion \\\n", "0 0.0 0.000000 0.0 0.0 \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 0.0 0.072289 0.0 0.0 \n", "4 0.0 0.000000 0.0 0.0 \n", "\n", " TD_rest TD_russia TD_science TD_science_education TD_shops \\\n", "0 0.000000 0.000000 0.0 0.066667 0.000000 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.012048 0.024096 0.0 0.000000 0.060241 \n", "4 0.000000 0.000000 0.0 0.000000 0.125000 \n", "\n", " TD_slimming TD_society TD_soft TD_softporno_porno TD_sport_and_health \\\n", "0 0.0 0.000000 0.0 0.0 0.0 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.012048 0.0 0.0 0.0 \n", "4 0.0 0.000000 0.0 0.0 0.0 \n", "\n", " TD_sport_diet TD_sport_other TD_start_ups TD_tech_IT TD_technologies \\\n", "0 0.0 0.0 0.0 0.0 0.066667 \n", "1 NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN \n", "3 0.0 0.0 0.0 0.0 0.000000 \n", "4 0.0 0.0 0.0 0.0 0.000000 \n", "\n", " TD_thoughts_ideas TD_tourism TD_travel TD_TV TD_ukraine TD_video \\\n", "0 0.0 0.0 0.000 0.000000 0.0 0.0 \n", "1 NaN NaN NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN NaN NaN \n", "3 0.0 0.0 0.000 0.024096 0.0 0.0 \n", "4 0.0 0.0 0.125 0.000000 0.0 0.0 \n", "\n", " TD_way_of_life TD_wedding_communities TD_women_communities TD_workout \\\n", "0 0.066667 0.0 0.000000 0.0 \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 0.000000 0.0 0.036145 0.0 \n", "4 0.000000 0.0 0.000000 0.0 \n", "\n", " TD_youth_communities TD_sum animal_owner \n", "0 0.2 15.0 0.0 \n", "1 NaN NaN NaN \n", "2 NaN NaN NaN \n", "3 0.0 83.0 0.0 \n", "4 0.0 8.0 0.0 " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "day2[:5]" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "### сделать признаковую матрицу" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from time import time\n", "\n", "def make_feature_matrix(data):\n", " tm = time()\n", " \n", " data.fillna(-2, inplace=True)\n", " data.replace('-', -1, inplace=True)\n", " data.gender = data.gender.map({'F': -1, 'M': +1, -2: 0})\n", " data.MaxRegDate = pd.to_datetime(data.MaxRegDate.replace(-1, datetime.datetime(2010, 6, 6, 0, 0)).replace(-2, datetime.datetime(2009, 7, 7, 0, 0)))\n", " data.MinRegDate = pd.to_datetime(data.MinRegDate.replace(-1, datetime.datetime(2010, 6, 6, 0, 0)).replace(-2, datetime.datetime(2009, 7, 7, 0, 0)))\n", " # print (tmp.max()) # Timestamp('2015-09-08 00:00:00') 2015-08-17 00:00:00\n", " # print (tmp.min()) # Timestamp('2006-03-06 00:00:00') 2006-03-04 00:00:00\n", " data['deltatime'] = data.MaxRegDate - data.MinRegDate\n", " data.deltatime = data.deltatime.dt.total_seconds() /(60*60*24)\n", " data.MaxRegDate = (data.MaxRegDate - pd.to_datetime('2006-01-01T00:00:00.000000000')).dt.total_seconds() /(60*60*24)\n", " data.MinRegDate = (data.MinRegDate - pd.to_datetime('2006-01-01T00:00:00.000000000')).dt.total_seconds() /(60*60*24)\n", " \n", " data = data.astype(float)\n", " \n", " print ('time = ' + str(time() - tm))\n", " return (data)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "time = 6.3446221351623535\n", "time = 2.0537281036376953\n", "time = 2.0606093406677246\n" ] } ], "source": [ "data = make_feature_matrix(data)\n", "day1 = make_feature_matrix(day1)\n", "day2 = make_feature_matrix(day2)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(390000, 198) (130000, 198) (132016, 198)\n" ] } ], "source": [ "print (data.shape, day1.shape, day2.shape)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# подготовить матрицу для обучения\n", "def make_trainmatrix(data):\n", " ids = data.ID.values\n", " if 'y' in data.columns:\n", " X = data.drop(['ID', 'NetSales', 'y'], axis=1)\n", " else:\n", " X = data.drop(['ID', 'NetSales'], axis=1)\n", " y = np.log(data.NetSales.values + 1.0)\n", " \n", " return (X, y, ids)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import scipy.stats as ss\n", "\n", " \n", "# сделать ставки\n", "def make_rates(a):\n", " v_sum = 2500000 # общее число денег\n", " k = 8 # число игроков\n", " n = len(a) # число юзеров\n", " b = np.linspace(0, 1, n)\n", " b = v_sum * k * b / np.sum(b)\n", " b = b[ss.rankdata(a, method='ordinal') - 1] #np.argsort(a)\n", " \n", " return (b)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import scipy.stats as ss\n", "\n", " \n", "# сделать ставки - другая стратегия\n", "def make_rates(a):\n", " v_sum = 2500000 # общее число денег\n", " k = 12 # число игроков\n", " n = len(a) # число юзеров\n", " b = np.linspace(-1, 1, n)\n", " b = np.maximum(b, 0)\n", " b = v_sum * k * b / np.sum(b)\n", " b = np.maximum(b, 1)\n", " b = b[ss.rankdata(a, method='ordinal') - 1] #np.argsort(a)\n", " #b = np.round(b, 2)\n", " \n", " return (b)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "array([ 1.00000000e+00, 1.00000000e+00, 1.00000000e+00,\n", " 3.33333333e+06, 1.00000000e+07, 1.66666667e+07])" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "make_rates([1,2,10, 20, 30, 40])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": true }, "outputs": [], "source": [ "tmp = day2.columns.tolist()\n", "tmp[1] = 'NetSales' # там некорректность в значениях\n", "day2.columns = tmp\n", "\n", "X, y, data_ids = make_trainmatrix(data)\n", "X1, y1, day1_ids = make_trainmatrix(day1)\n", "X2, y2, day2_ids = make_trainmatrix(day2)" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " gender ActivityIndex Alcohol AverageFriendsRegMonthDelta \\\n", "0 -1.0 -1.00 0.0 92.0 \n", "1 -1.0 -1.00 0.0 -1.0 \n", "2 -1.0 -1.00 0.0 96.0 \n", "3 1.0 4.58 0.0 89.0 \n", "4 -1.0 5.74 0.0 97.0 \n", "\n", " CanSeeAllPosts CanSeeAllPosts_CanPost EducationType EducationType_VK \\\n", "0 -1.0 -1.0 12.0 -1.0 \n", "1 -1.0 -1.0 -1.0 -1.0 \n", "2 -1.0 -1.0 12.0 -1.0 \n", "3 0.0 1.0 0.0 0.0 \n", "4 0.0 1.0 -1.0 -1.0 \n", "\n", " FriendsAverageDeletedAccounts FriendsAverageHasHighSchools \\\n", "0 0.06667 0.33333 \n", "1 0.00000 0.33333 \n", "2 0.11579 0.45263 \n", "3 0.02691 0.72197 \n", "4 0.01754 0.62500 \n", "\n", " FriendsAverageHasJobs FriendsPerDay HasPhone HasSkype HasTwitter \\\n", "0 0.06667 0.01768 0.0 0.0 0.0 \n", "1 0.22222 -1.00000 0.0 0.0 0.0 \n", "2 0.06316 0.03699 0.0 0.0 0.0 \n", "3 0.10762 0.07254 0.0 0.0 0.0 \n", "4 0.33114 0.15117 0.0 0.0 0.0 \n", "\n", " LastActivity LifeTime MaxRegDate MinRegDate MobileUsageAll \\\n", "0 113.0 2623.0 2483.0 749.0 -1.00000 \n", "1 79.0 -1.0 903.0 903.0 -1.00000 \n", "2 145.0 2514.0 779.0 779.0 -1.00000 \n", "3 3.0 2578.0 907.0 890.0 0.93583 \n", "4 0.0 2785.0 697.0 697.0 0.51657 \n", "\n", " MobileUsageAndroid MobileUsageIPad MobileUsageIphone \\\n", "0 -1.0 -1.00000 -1.00000 \n", "1 -1.0 -1.00000 -1.00000 \n", "2 -1.0 -1.00000 -1.00000 \n", "3 0.0 0.65714 0.10857 \n", "4 0.0 0.00000 0.98930 \n", "\n", " MobileUsageWinPhone MonthsFromMaxRegDate MonthsFromMinRegDate \\\n", "0 -1.0 51.0 108.0 \n", "1 -1.0 103.0 103.0 \n", "2 -1.0 107.0 107.0 \n", "3 0.0 103.0 103.0 \n", "4 0.0 110.0 110.0 \n", "\n", " NumberOfAccounts NumberOfAccountsMOIMIR NumberOfAccountsODKL \\\n", "0 2.0 0.0 2.0 \n", "1 1.0 1.0 0.0 \n", "2 1.0 0.0 1.0 \n", "3 2.0 1.0 0.0 \n", "4 1.0 0.0 0.0 \n", "\n", " NumberOfAccountsVK NumberOfAdvancedSchools NumberOfChilds \\\n", "0 0.0 0.0 0.0 \n", "1 0.0 0.0 0.0 \n", "2 0.0 0.0 0.0 \n", "3 1.0 2.0 0.0 \n", "4 1.0 0.0 0.0 \n", "\n", " NumberOfChilds_VK NumberOfCompanies 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1283.0 -2.00000 \n", "1 1.0 2261.0 2992.0 1276.0 0.95402 \n", "2 21.0 1003.0 2390.0 815.0 -1.00000 \n", "3 0.0 2869.0 815.0 606.0 0.85795 \n", "4 74.0 -1.0 1204.0 1204.0 -1.00000 \n", "\n", " MobileUsageAndroid MobileUsageIPad MobileUsageIphone \\\n", "0 -2.00000 -2.0 -2.00000 \n", "1 0.91429 0.0 0.59036 \n", "2 -1.00000 -1.0 -1.00000 \n", "3 0.00000 0.0 0.99338 \n", "4 -1.00000 -1.0 -1.00000 \n", "\n", " MobileUsageWinPhone MonthsFromMaxRegDate MonthsFromMinRegDate \\\n", "0 -2.0 -2.0 -2.0 \n", "1 0.0 34.0 91.0 \n", "2 -1.0 54.0 106.0 \n", "3 0.0 106.0 113.0 \n", "4 -1.0 93.0 93.0 \n", "\n", " NumberOfAccounts NumberOfAccountsMOIMIR NumberOfAccountsODKL \\\n", "0 -2.0 -2.0 -2.0 \n", "1 7.0 1.0 3.0 \n", "2 3.0 1.0 2.0 \n", "3 2.0 1.0 0.0 \n", "4 1.0 1.0 0.0 \n", "\n", " NumberOfAccountsVK NumberOfAdvancedSchools NumberOfChilds \\\n", "0 -2.0 -2.0 -2.0 \n", "1 3.0 0.0 0.0 \n", "2 0.0 0.0 0.0 \n", "3 1.0 0.0 0.0 \n", "4 0.0 0.0 0.0 \n", "\n", " NumberOfChilds_VK NumberOfCompanies NumberOfDeletedAccounts \\\n", "0 -2.0 -2.0 -2.0 \n", "1 0.0 0.0 0.0 \n", "2 -1.0 0.0 0.0 \n", "3 0.0 0.0 0.0 \n", "4 -1.0 0.0 0.0 \n", "\n", " NumberOfDeletedAccounts_VK NumberOfEntrance NumberOfFollowers \\\n", "0 -2.0 -2.0 -2.0 \n", "1 0.0 151.0 2.0 \n", "2 -1.0 -1.0 -1.0 \n", "3 0.0 137.0 121.0 \n", "4 -1.0 -1.0 -1.0 \n", "\n", " NumberOfFriendsMax NumberOfFriendsMax_VK NumberOfFriendsMin \\\n", "0 -2.0 -2.0 -2.0 \n", "1 270.0 111.0 0.0 \n", "2 44.0 -1.0 1.0 \n", "3 128.0 128.0 6.0 \n", "4 15.0 -1.0 15.0 \n", "\n", " NumberOfFriendsSum NumberOfGroupsMax NumberOfGroupsSum_OK \\\n", "0 -2.0 -2.0 -2.0 \n", "1 826.0 12.0 12.0 \n", "2 61.0 -1.0 -1.0 \n", "3 134.0 1.0 -1.0 \n", "4 15.0 20.0 -1.0 \n", "\n", " NumberOfHighSchools NumberOfNotesMax NumberOfPhotosMax \\\n", "0 -2.0 -2.0 -2.0 \n", "1 0.0 79.0 20.0 \n", "2 2.0 1.0 32.0 \n", "3 2.0 -1.0 371.0 \n", "4 2.0 -1.0 1.0 \n", "\n", " NumberOfPhotosMin_VK NumberOfPrivateAccounts NumberOfPrivateAccounts_OK \\\n", "0 -2.0 -2.0 -2.0 \n", "1 1.0 1.0 1.0 \n", "2 -1.0 0.0 0.0 \n", "3 371.0 0.0 -1.0 \n", "4 -1.0 0.0 -1.0 \n", "\n", " NumberOfRelatives NumberOfRelatives_OK NumberOfSchools \\\n", "0 -2.0 -2.0 -2.0 \n", "1 16.0 28.0 2.0 \n", "2 0.0 0.0 1.0 \n", "3 2.0 -1.0 2.0 \n", "4 0.0 -1.0 1.0 \n", "\n", " NumberOfSubscriptions NumberOfVideos Relation SaScore1 SaScore2 \\\n", "0 -2.0 -2.0 -2.0 -2.00000 -2.00000 \n", "1 6.0 -1.0 6.0 -1.90297 -1.72063 \n", "2 -1.0 -1.0 0.0 -3.57804 -1.89699 \n", "3 167.0 1012.0 0.0 -4.58583 -3.21992 \n", "4 -1.0 2.0 0.0 -4.70057 -2.19835 \n", "\n", " SaScore5 SaScore6 SaScore7 SaScoreFraud SaScoreSocial Smoking \\\n", "0 -2.00000 -2.00000 -2.0 -2.00000 -2.00000 -2.0 \n", "1 -3.57124 -5.03950 155.0 -2.39785 -2.97663 0.0 \n", "2 -4.78375 -6.30990 124.0 -3.51037 -4.46552 0.0 \n", "3 -5.37974 -7.15375 76.0 -4.51827 -5.15266 0.0 \n", "4 -5.85025 -7.95237 91.0 -5.07033 -4.69854 0.0 \n", "\n", " UseScreenName Worldviews YearsSinceMinRegDate YearsSinceMinRegDate_OK \\\n", "0 -2.0 -2.0 -2.00000 -2.00000 \n", "1 1.0 0.0 7.57670 7.57379 \n", "2 0.0 0.0 8.83984 4.80161 \n", "3 1.0 0.0 9.41240 -1.00000 \n", "4 0.0 0.0 7.77480 -1.00000 \n", "\n", " YearsSinceMinRegDate_VK NumberOfAccountsFB Interest_1 Interest_2 \\\n", "0 -2.0000 1.0 -2.0 -2.0 \n", "1 7.5767 1.0 0.0 5.0 \n", "2 -1.0000 -2.0 -1.0 -1.0 \n", "3 9.4124 -2.0 1.0 3.0 \n", "4 -1.0000 -2.0 -1.0 -1.0 \n", "\n", " Interest_3 Interest_4 Interest_5 Interest_6 Interest_7 Interest_8 \\\n", "0 -2.0 -2.0 -2.0 -2.0 -2.0 -2.0 \n", "1 0.0 0.0 5.0 0.0 6.0 0.0 \n", "2 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 \n", "3 2.0 3.0 4.0 3.0 6.0 6.0 \n", "4 -1.0 -1.0 -1.0 -1.0 -1.0 -1.0 \n", "\n", " Interest_9 Interest_10 Interest_11 Interest_12 Interest_13 \\\n", "0 -2.0 -2.0 -2.0 -2.0 -2.0 \n", "1 5.0 2.0 6.0 0.0 5.0 \n", "2 -1.0 -1.0 -1.0 -1.0 -1.0 \n", "3 7.0 8.0 4.0 2.0 5.0 \n", "4 -1.0 -1.0 -1.0 -1.0 -1.0 \n", "\n", " Interest_14 Interest_15 Interest_16 Interest_17 Interest_18 \\\n", "0 -2.0 -2.0 -2.0 -2.0 -2.0 \n", "1 0.0 7.0 0.0 0.0 0.0 \n", "2 -1.0 -1.0 -1.0 -1.0 -1.0 \n", "3 2.0 6.0 0.0 7.0 5.0 \n", "4 -1.0 -1.0 -1.0 -1.0 -1.0 \n", "\n", " Interest_19 Interest_20 Interest_21 Interest_22 Interest_23 \\\n", "0 -2.0 -2.0 -2.0 -2.0 -2.0 \n", "1 0.0 0.0 0.0 0.0 0.0 \n", "2 -1.0 -1.0 -1.0 -1.0 -1.0 \n", "3 0.0 0.0 0.0 0.0 0.0 \n", "4 -1.0 -1.0 -1.0 -1.0 -1.0 \n", "\n", " Interest_24 Interest_25 TD_acquaint_communic TD_acquaintances \\\n", "0 -2.0 -2.0 -2.000000 -2.0 \n", "1 0.0 1.0 0.011765 0.0 \n", "2 -1.0 -1.0 -2.000000 -2.0 \n", "3 0.0 0.0 0.006502 0.0 \n", "4 -1.0 -1.0 -2.000000 -2.0 \n", "\n", " TD_active_rest TD_ad TD_animals TD_anime_hentai TD_architecture \\\n", "0 -2.0000 -2.000000 -2.0000 -2.000000 -2.0 \n", "1 0.0000 0.011765 0.0000 0.011765 0.0 \n", "2 -2.0000 -2.000000 -2.0000 -2.000000 -2.0 \n", "3 0.0013 0.002601 0.0013 0.001300 0.0 \n", "4 -2.0000 -2.000000 -2.0000 -2.000000 -2.0 \n", "\n", " TD_art_design TD_beautiful_girls TD_beauty TD_books TD_business \\\n", "0 -2.000000 -2.0 -2.000000 -2.000000 -2.000000 \n", "1 0.047059 0.0 0.000000 0.000000 0.023529 \n", "2 -2.000000 -2.0 -2.000000 -2.000000 -2.000000 \n", "3 0.049415 0.0 0.019506 0.016905 0.046814 \n", "4 -2.000000 -2.0 -2.000000 -2.000000 -2.000000 \n", "\n", " TD_cars TD_cartoons TD_caucasian TD_celebrities TD_children \\\n", "0 -2.000000 -2.0000 -2.0 -2.000000 -2.0 \n", "1 0.000000 0.0000 0.0 0.000000 0.0 \n", "2 -2.000000 -2.0000 -2.0 -2.000000 -2.0 \n", "3 0.003901 0.0013 0.0 0.010403 0.0 \n", "4 -2.000000 -2.0000 -2.0 -2.000000 -2.0 \n", "\n", " TD_cognitive TD_companies TD_computers TD_cookery TD_design \\\n", "0 -2.000000 -2.0 -2.0000 -2.000000 -2.000000 \n", "1 0.023529 0.0 0.0000 0.011765 0.011765 \n", "2 -2.000000 -2.0 -2.0000 -2.000000 -2.000000 \n", "3 0.046814 0.0 0.0013 0.006502 0.013004 \n", "4 -2.000000 -2.0 -2.0000 -2.000000 -2.000000 \n", "\n", " TD_design_renovation TD_diets TD_do_yourself \\\n", "0 -2.0000 -2.000000 -2.000000 \n", "1 0.0000 0.000000 0.000000 \n", "2 -2.0000 -2.000000 -2.000000 \n", "3 0.0013 0.002601 0.007802 \n", "4 -2.0000 -2.000000 -2.000000 \n", "\n", " TD_electronics_electrappliances TD_entertainment TD_family_home \\\n", "0 -2.0 -2.000000 -2.000000 \n", "1 0.0 0.047059 0.000000 \n", "2 -2.0 -2.000000 -2.000000 \n", "3 0.0 0.074122 0.015605 \n", "4 -2.0 -2.000000 -2.000000 \n", "\n", " TD_fashion TD_finance TD_fitness TD_football TD_foreign_lang \\\n", "0 -2.000000 -2.000000 -2.000000 -2.000000 -2.000000 \n", "1 0.011765 0.023529 0.000000 0.011765 0.011765 \n", "2 -2.000000 -2.000000 -2.000000 -2.000000 -2.000000 \n", "3 0.009103 0.006502 0.003901 0.000000 0.014304 \n", "4 -2.000000 -2.000000 -2.000000 -2.000000 -2.000000 \n", "\n", " TD_gadgets TD_games TD_geopolitics_economy TD_gif TD_goods_services \\\n", "0 -2.0 -2.0 -2.0 -2.0 -2.000000 \n", "1 0.0 0.0 0.0 0.0 0.105882 \n", "2 -2.0 -2.0 -2.0 -2.0 -2.000000 \n", "3 0.0 0.0 0.0 0.0 0.016905 \n", "4 -2.0 -2.0 -2.0 -2.0 -2.000000 \n", "\n", " TD_hobbies TD_horoscope TD_horror TD_humour TD_images TD_insurance \\\n", "0 -2.000000 -2.000000 -2.0 -2.000000 -2.000000 -2.0 \n", "1 0.000000 0.000000 0.0 0.035294 0.000000 0.0 \n", "2 -2.000000 -2.000000 -2.0 -2.000000 -2.000000 -2.0 \n", "3 0.011704 0.002601 0.0 0.015605 0.020806 0.0 \n", "4 -2.000000 -2.000000 -2.0 -2.000000 -2.000000 -2.0 \n", "\n", " TD_interior TD_kazakhstan TD_landscape_design TD_literature_poetry \\\n", "0 -2.000000 -2.0 -2.000000 -2.000000 \n", "1 0.000000 0.0 0.023529 0.000000 \n", "2 -2.000000 -2.0 -2.000000 -2.000000 \n", "3 0.007802 0.0 0.000000 0.023407 \n", "4 -2.000000 -2.0 -2.000000 -2.000000 \n", "\n", " TD_mass_media TD_mass_media_ad_PR TD_men_communities TD_mobile_internet \\\n", "0 -2.0000 -2.000000 -2.000000 -2.000000 \n", "1 0.0000 0.011765 0.011765 0.011765 \n", "2 -2.0000 -2.000000 -2.000000 -2.000000 \n", "3 0.0013 0.014304 0.019506 0.000000 \n", "4 -2.0000 -2.000000 -2.000000 -2.000000 \n", "\n", " TD_motivation TD_moto TD_movies TD_music TD_names TD_nature \\\n", "0 -2.000000 -2.0000 -2.000000 -2.000000 -2.0 -2.000000 \n", "1 0.000000 0.0000 0.035294 0.000000 0.0 0.011765 \n", "2 -2.000000 -2.0000 -2.000000 -2.000000 -2.0 -2.000000 \n", "3 0.039012 0.0013 0.040312 0.014304 0.0 0.002601 \n", "4 -2.000000 -2.0000 -2.000000 -2.000000 -2.0 -2.000000 \n", "\n", " TD_nature_and_travel TD_nostalgia TD_other_services \\\n", "0 -2.000000 -2.0000 -2.000000 \n", "1 0.011765 0.0000 0.011765 \n", "2 -2.000000 -2.0000 -2.000000 \n", "3 0.018205 0.0013 0.003901 \n", "4 -2.000000 -2.0000 -2.000000 \n", "\n", " TD_parents_communities TD_philosophy_esoterics TD_photo TD_poetry \\\n", "0 -2.000000 -2.000000 -2.000000 -2.000000 \n", "1 0.000000 0.000000 0.011765 0.000000 \n", "2 -2.000000 -2.000000 -2.000000 -2.000000 \n", "3 0.005202 0.016905 0.007802 0.006502 \n", "4 -2.000000 -2.000000 -2.000000 -2.000000 \n", "\n", " TD_politics TD_professions TD_proposed_news TD_real_estate \\\n", "0 -2.0 -2.000000 -2.000000 -2.000000 \n", "1 0.0 0.023529 0.011765 0.011765 \n", "2 -2.0 -2.000000 -2.000000 -2.000000 \n", "3 0.0 0.009103 0.006502 0.002601 \n", "4 -2.0 -2.000000 -2.000000 -2.000000 \n", "\n", " TD_regional_communities TD_relations TD_religion TD_rest TD_russia \\\n", "0 -2.000000 -2.000000 -2.0 -2.000000 -2.000000 \n", "1 0.082353 0.000000 0.0 0.000000 0.035294 \n", "2 -2.000000 -2.000000 -2.0 -2.000000 -2.000000 \n", "3 0.045514 0.009103 0.0 0.020806 0.016905 \n", "4 -2.000000 -2.000000 -2.0 -2.000000 -2.000000 \n", "\n", " TD_science TD_science_education TD_shops TD_slimming TD_society \\\n", "0 -2.000000 -2.000000 -2.000000 -2.000000 -2.000000 \n", "1 0.000000 0.058824 0.082353 0.000000 0.023529 \n", "2 -2.000000 -2.000000 -2.000000 -2.000000 -2.000000 \n", "3 0.002601 0.066320 0.006502 0.003901 0.009103 \n", "4 -2.000000 -2.000000 -2.000000 -2.000000 -2.000000 \n", "\n", " TD_soft TD_softporno_porno TD_sport_and_health TD_sport_diet \\\n", "0 -2.000000 -2.000000 -2.000000 -2.0000 \n", "1 0.023529 0.000000 0.023529 0.0000 \n", "2 -2.000000 -2.000000 -2.000000 -2.0000 \n", "3 0.005202 0.002601 0.014304 0.0013 \n", "4 -2.000000 -2.000000 -2.000000 -2.0000 \n", "\n", " TD_sport_other TD_start_ups TD_tech_IT TD_technologies \\\n", "0 -2.0000 -2.0000 -2.000000 -2.000000 \n", "1 0.0000 0.0000 0.035294 0.023529 \n", "2 -2.0000 -2.0000 -2.000000 -2.000000 \n", "3 0.0013 0.0013 0.006502 0.002601 \n", "4 -2.0000 -2.0000 -2.000000 -2.000000 \n", "\n", " TD_thoughts_ideas TD_tourism TD_travel TD_TV TD_ukraine TD_video \\\n", "0 -2.000000 -2.000000 -2.000000 -2.000000 -2.0 -2.000000 \n", "1 0.000000 0.000000 0.000000 0.000000 0.0 0.000000 \n", "2 -2.000000 -2.000000 -2.000000 -2.000000 -2.0 -2.000000 \n", "3 0.005202 0.003901 0.014304 0.010403 0.0 0.005202 \n", "4 -2.000000 -2.000000 -2.000000 -2.000000 -2.0 -2.000000 \n", "\n", " TD_way_of_life TD_wedding_communities TD_women_communities TD_workout \\\n", "0 -2.000000 -2.0 -2.000000 -2.000000 \n", "1 0.000000 0.0 0.011765 0.011765 \n", "2 -2.000000 -2.0 -2.000000 -2.000000 \n", "3 0.014304 0.0 0.033810 0.003901 \n", "4 -2.000000 -2.0 -2.000000 -2.000000 \n", "\n", " TD_youth_communities TD_sum animal_owner deltatime \n", "0 -2.000000 -2.0 -2.0 0.0 \n", "1 0.000000 85.0 0.0 1716.0 \n", "2 -2.000000 -2.0 -2.0 1575.0 \n", "3 0.019506 769.0 1.0 209.0 \n", "4 -2.000000 -2.0 -2.0 0.0 " ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X1[:5]" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn.ensemble import RandomForestRegressor\n", "\n", "rf = RandomForestRegressor(n_estimators=1000,\n", " criterion='mse', max_depth=None,\n", " min_samples_split=200, min_samples_leaf=100,\n", " min_weight_fraction_leaf=0.0,\n", " max_features=20, max_leaf_nodes=None,\n", " min_impurity_split=1e-07, bootstrap=True,\n", " oob_score=False, n_jobs=-1, random_state=10, # None\n", " verbose=0, warm_start=False)\n", "\n", "rf.fit(X, y)\n", "a1_rf = rf.predict(X1)\n", "a2_rf = rf.predict(X2)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/alexander/anaconda3/lib/python3.5/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n", " \"This module will be removed in 0.20.\", DeprecationWarning)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "0\n", "1\n", "2\n", "3\n", "4\n", "5\n", "6\n", "7\n", "8\n", "9\n" ] } ], "source": [ "from xgboost import XGBRegressor\n", "\n", "#a1_gbm = 0\n", "a2_gbm = 0\n", "\n", "for t in range(10):\n", " gbm = XGBRegressor(max_depth=4, learning_rate=0.1,\n", " n_estimators=100, silent=True,\n", " objective='reg:linear', gamma=0.6,\n", " min_child_weight=5, max_delta_step=0,\n", " subsample=0.8, colsample_bytree=0.8,\n", " colsample_bylevel=1, reg_alpha=0,\n", " reg_lambda=1, scale_pos_weight=1, base_score=0.5,\n", " seed=t, missing=None)\n", " gbm.fit(X, y)\n", " a1_gbm += gbm.predict(X1)\n", " a2_gbm += gbm.predict(X2)\n", " print (t)\n", "\n", "\n", "#a1_gbm /= 5\n", "a2_gbm /= 10" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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YkACkpKg7A/K8pJTqQ9vyamtt+POfbRg3jpkHqb1O6v04ZuXKld29hC6B4ow9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Xz9\n9dcBr+nevTu6d+8eAetCR1VVFWbOnIkuXbqgffv2aNGiBSwWC7799ltcv34dffv2xR/+8IdIm0k0\ngL///e+4cuUK7rrrLiQkJMBkMqGiogLXrl3DmDFjZFPRnpqaihEjRmDz5s14/fXX0atXL1y4cAHf\nfvutJJ0tN7Zu3QoAty2KRkE/xDAMg5kzZ6KoqAgHDhzAwYMH0bp1azz77LOyfAB9kds5d01NjVSf\nESzgA8DYsWObfdBv06YNRo0ahUOHDuHgwYOwWq3Q6/Xo0KEDJkyYgH79+kXaRKKBPPbYY9ixYwcq\nKipgsVhgMBjQuXNnPPvss+jdu3ekzQspEyZMQOvWrbF9+3Zs3rwZMTExSE9PR2ZmpuyO4sSumm7d\nuqFDhw63dQ+GV1LpKkEQBEEoGPlqiBIEQRAE4QcFfYIgCIJQCBT0CYIgCEIhUNAnCIIgCIVAQZ8g\nCIIgFAIFfYIgCIJQCBT0CYIgCEIhUNAnCIIgCIVAQZ8gCIIgFAIFfYIgCIJQCBT0CYIgCEIhUNAn\nCIIgCIVAQZ8gCIIgFML/B1t6shCp3jWYAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "figsize(6, 5)\n", "plt.scatter(a1_gbm, a1_rf)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import lightgbm as lgb\n", "from sklearn.model_selection import cross_val_score\n", "from sklearn.model_selection import cross_val_predict\n", "\n", "lgbm = lgb.LGBMRegressor(learning_rate=0.1, n_estimators=50, nthread=-1, seed=0)\n", "\n", "\n", "lgbm.fit(X, y)\n", "\n", "a1_lgbm = lgbm.predict(X1)\n", "a2_lgbm = lgbm.predict(X2)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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8XFqEqdxoRG6uEj/5SRY0Gjny85VIT5eirS3GktBesHl4b59SRvpkEg4oUBMSZjQaOWbP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\nHAVqQggJcxSoCSEkzFGgJoSQMEeBmhBCwpzI5XK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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(a1_rf, a1_lgbm, 10, c ='#0000AA')" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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DbSF21yhhMHgO/M733bGjnntdvb6/qJltWPF0bmFLixXr1+sFtzkcQGwsIu6UFWcqlTRi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\njhpggvWiRWqkpzPVHXK5MC9aVdUZ9UE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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(a2_rf, a2_lgbm, 10, c ='#0000AA')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": false }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 28, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# a1 = 0.2 * a1_rf + 0.8 * a1_gbm\n", "# a2 = 0.2 * a2_rf + 0.8 * a2_gbm\n", "\n", "\n", "a1 = 0.2 * a1_rf + 0.8 * a1_lgbm\n", "a2 = 0.2 * a2_rf + 0.8 * a2_lgbm" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(0.56006001304460185,\n", " 6.1910533431351009,\n", " 0.56006001304460185,\n", " 6.3666864883953096)" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "min(a1), max(a1), min(a1), max(a2)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "581.12574924935996" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "max(np.exp(a2) - 1.0)" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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BidIDNetSales_Forecast
0192.205029390004.020.042152
19.543269390010.03.507976
2124.289713390016.015.434077
3256.170018390022.036.039177
4213.840698390028.020.102014
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" ], "text/plain": [ " Bid ID NetSales_Forecast\n", "0 192.205029 390004.0 20.042152\n", "1 9.543269 390010.0 3.507976\n", "2 124.289713 390016.0 15.434077\n", "3 256.170018 390022.0 36.039177\n", "4 213.840698 390028.0 20.102014" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df1 = pd.DataFrame({'ID': day1_ids, 'NetSales_Forecast': ((np.exp(a1) - 1.0)), 'Bid': (make_rates(a1))})\n", "# df1 = df1.astype(int)\n", "df1.to_excel('ans_dyakonov_day1_post.xlsx', index=False, columns=['ID', 'NetSales_Forecast', 'Bid'])\n", "df1[:5]" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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BidIDNetSales_Forecast
0123.600448520001.015.652646
182.177669520007.011.477249
272.586258520013.010.330755
3127.380551520019.016.292125
4220.999519520025.022.989423
\n", "
" ], "text/plain": [ " Bid ID NetSales_Forecast\n", "0 123.600448 520001.0 15.652646\n", "1 82.177669 520007.0 11.477249\n", "2 72.586258 520013.0 10.330755\n", "3 127.380551 520019.0 16.292125\n", "4 220.999519 520025.0 22.989423" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df2 = pd.DataFrame({'ID': day2_ids, 'NetSales_Forecast': ((np.exp(a2) - 1.0)), 'Bid': (make_rates(a2))})\n", "# df2 = df2.astype(int)\n", "df2.to_excel('ans_dyakonov_day2_post.xlsx', index=False, columns=['ID', 'NetSales_Forecast', 'Bid'])\n", "df2[:5]" ] }, { "cell_type": "markdown", "metadata": { "collapsed": false }, "source": [ "## Дальше проверка (для себя)" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "collapsed": true }, "outputs": [], "source": [ "tmp1 = pd.read_excel('dyakonov_day1.xlsx')" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "collapsed": false }, "outputs": [], "source": [ "tmp2 = pd.read_excel('dyakonov_day2.xlsx')" ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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IDNetSales_ForecastBid
052000114126
152000712101
2520013974
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" ], "text/plain": [ " ID NetSales_Forecast Bid\n", "0 520001 14 126\n", "1 520007 12 101\n", "2 520013 9 74" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tmp2[:3]" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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w2eaGW4to4/Y0QXcAGW4qqyzDbQSyvakrZPOWInUWlOF3A81ok79P37DH9qau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\nCCEZSsKyLJvsk5jsnXfeSfYpEEKIKK1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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(tmp1.NetSales_Forecast, df1.NetSales_Forecast)" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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CzELjAfDikRYUZEuRLZMEeXnp1HKsml+auMaJSFgxWLhwIRYuXMh5fsuWLSGvr6mpQU1N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\nRDcItRynjbP4Euql5Koy5+OfXZaI3S5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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(tmp1.Bid, df1.Bid)" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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VV+mhmXbfUwEoNIoH2wy1yl8pE7jz1tXzdFiRb8DV83Qhz5l+w/ClYaRsqixE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\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(tmp2.NetSales_Forecast, df2.NetSales_Forecast)" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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qlaoqmaKiDEpKMhg0SJNZl+V6uXOtdVggIh1JytNPPx0zy+ZCR9iTvKSSLSDs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\npMmZkPZKNU1NEo2NmR9zOMjoHbNrV5y//1021qU3WurrmjatJ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hi6Frrj69atPs4+O8GL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HDh48SHV1NR988EHK8ccff5xZs2alHAuFQlRXVxspulAIJAlWrXIYbrDLlzuQJCgtVVBV+NWv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\n3o6ffvoJlZW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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.scatter(tmp2.Bid, df2.Bid)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# проверка" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(390000, 196) (292500, 196) (97500, 196) (390000,) (292500,) (97500,)\n" ] } ], "source": [ "def my_traintestsplit(X, y, p=0.25):\n", " n = X.shape[0]\n", " nn = int(np.round((1-p) * n))\n", " return (X[:nn], y[:nn], X[nn:], y[nn:])\n", "\n", "X1, y1, X2, y2 = my_traintestsplit(X, y)\n", "print (X.shape, X1.shape, X2.shape, y.shape, y1.shape, y2.shape)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn.ensemble import RandomForestRegressor\n", "\n", "rf = RandomForestRegressor(n_estimators=400,\n", " criterion='mse', max_depth=None,\n", " min_samples_split=200, min_samples_leaf=100,\n", " min_weight_fraction_leaf=0.0,\n", " max_features=20, max_leaf_nodes=None,\n", " min_impurity_split=1e-07, bootstrap=True,\n", " oob_score=False, n_jobs=-1, random_state=10, # None\n", " verbose=0, warm_start=False)\n", "\n", "rf.fit(X1, y1)\n", "a_rf = rf.predict(X2)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/home/alexander/anaconda3/lib/python3.5/site-packages/sklearn/cross_validation.py:44: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n", " \"This module will be removed in 0.20.\", DeprecationWarning)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "0\n", "1\n", "2\n", "3\n", "4\n" ] } ], "source": [ "from xgboost import XGBRegressor\n", "\n", "a_gbm = 0\n", "\n", "\n", "for t in range(5):\n", " gbm = XGBRegressor(max_depth=4, learning_rate=0.1,\n", " n_estimators=100, silent=True,\n", " objective='reg:linear', gamma=0.6,\n", " min_child_weight=5, max_delta_step=0,\n", " subsample=0.8, colsample_bytree=0.8,\n", " colsample_bylevel=1, reg_alpha=0,\n", " reg_lambda=1, scale_pos_weight=1, base_score=0.5,\n", " seed=t, missing=None)\n", " gbm.fit(X1, y1)\n", " a_gbm += gbm.predict(X2)\n", " print (t)\n", "\n", "\n", "a_gbm /= 5\n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": true }, "outputs": [], "source": [ "a = 0.2 * a_rf + 0.8 * a_gbm" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "collapsed": false }, "outputs": [ { "ename": "NameError", "evalue": "name 'a' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 35\u001b[0m \u001b[0mfigsize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m6\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m5\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 36\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 37\u001b[0;31m \u001b[0mdf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m'pred'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'test'\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0my2\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 38\u001b[0m \u001b[0mprint\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"Metric: \"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhackathone_metric\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mNameError\u001b[0m: name 'a' is not defined" ] } ], "source": [ "from scipy.integrate import trapz, simps\n", "\n", "def hackathone_metric(df, do_draw=True):\n", " '''На фход подается словарь с ответами алгоритма(поле pred) \n", " и фактическими значениями(поле test):\n", " df = {'pred': [2,3,55,63,1,2,100,100,10],'test': [1,2,3,4,5,0,99,121,14]}\n", " '''\n", "\n", " # Сортируем фактические продажи по возрастанию и считаем кумулятивную сумму – это нижняя линия\n", " n = range(1, len(df['test'])+1)\n", " c1 = np.cumsum(sorted(df['test'], reverse=False))\n", "\n", " # Сортируем фактические продажи по убыванию и считаем кумулятивную сумму – это верхняя линия\n", " c2 = np.cumsum(sorted(df['test'], reverse=True))\n", "\n", " # Площадь от верхней линии к нижней линии\n", " s1 = simps(c2, n) - simps(c1, n)\n", "\n", " # Теперь берём пары предсказаний и фактических продаж\n", " # Сортируем по возрастанию прогнозного значения\n", " c3 = np.cumsum(list(zip(*sorted(zip(df['pred'],df['test']), key=lambda x: x[0])))[1])\n", " s2 = simps(c3, n) - simps(c1, n)\n", " \n", " if do_draw:\n", " plt.plot(n,c1, label='Lower Line')\n", " plt.plot(n,c2, label='Upper Line')\n", " plt.plot(n,c3, label='Actual Line')\n", " plt.legend()\n", "\n", " return (1-s2/s1)\n", "\n", "\n", "# Проверка метрики - на вход подается полностью случайный прогноз\n", "# Ожидается, что искомая линия пройдет посередине\n", "figsize(6, 5)\n", "\n", "df = {'pred': a,'test': y2}\n", "print (\"Metric: \", hackathone_metric(df))" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Metric: 0.621995550395\n" ] }, { "data": { "image/png": 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Ph5GRUZt9CwsLATwu4oRC4Quv2ZHxCZEXsZjBlT/vwN7RDK69lecUdEIIIa3J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\nU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555Bk9PT6m5C/n7+1NQUEBubi51dXWcPn2azMxMMjMzGTBgAM8//7x9z7bU/dZlZmbS\nr18/p0eudKXadiRXNXop1589Kjrk2rVrrF+/nv3792MwGAgJCSExMZHp06e7OzW3qq+vJy0t7aYx\nKSkpzJ49G2h7aOe6des4evQoVquV8PBwUlJSGDFihNPriouL+fbbbzl37hxeXl6MHDmS+fPnt3u+\nQFZWFjt27KCurg4/Pz9iY2PR6XROhwy76zweO3aMN954w+khv1Jv18rOzmbHjh1UV1fj6+tLTEwM\nqampDndKlpq7TnFxMdu2beP06dMYjUYCAgKIi4tj5syZTnu2pe635oUXXiAkJITly5c7LetKte1I\nrr9HGichhBBCCJXkHCchhBBCCJWkcRJCCCGEUEkaJyGEEEIIlaRxEkIIIYRQSRonIYQQQgiVpHES\nQgghhFBJGichhBBCCJWkcRJCCCGEUEkaJyGEEEIIlaRxEkIIIYRQSRonIYQQQgiVpHESQgghhFBJ\nGichhBBCCJX+HykS9N7mfxNVAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df = {'pred': (np.round(np.exp(a) - 1.0)),'test': y2}\n", "print (\"Metric: \", hackathone_metric(df))" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.0 0.620636518173\n", "0.0526315789474 0.620832841581\n", "0.105263157895 0.621046803985\n", "0.157894736842 0.621295643409\n", "0.210526315789 0.621516542351\n", "0.263157894737 0.621659999279\n", "0.315789473684 0.621783133362\n", "0.368421052632 0.62191612081\n", "0.421052631579 0.622068011626\n", "0.473684210526 0.622145190819\n", "0.526315789474 0.622153453196\n", "0.578947368421 0.622204900991\n", "0.631578947368 0.622256660367\n", "0.684210526316 0.62218627885\n", "0.736842105263 0.622107463885\n", "0.789473684211 0.622116445131\n", "0.842105263158 0.622126191117\n", "0.894736842105 0.622081835009\n", "0.947368421053 0.622031330678\n", "1.0 0.621928255973\n" ] }, { "data": { "text/plain": [ "[]" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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SMl9lQzNeOXIVw4Pc8eDoWz+PhpmLx8zFY+aWoVKp8OvRQXhmah8c+LECrx25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\nubKwqRGguKYRiWfLsHBEIAI9nKQuR5Y47VI8Zi4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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "linsp = np.linspace(0, 1, 20)\n", "e = []\n", "\n", "for alpha in linsp:\n", " \n", " c = (alpha) * a_gbm + (1 - alpha) * a_rf\n", " df = {'pred': c,'test': y2}\n", " score = hackathone_metric(df, do_draw=False)\n", " e.append(score)\n", " print (alpha, score)\n", " \n", "plt.plot(linsp, e)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [default]", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.5.2" } }, "nbformat": 4, "nbformat_minor": 1 }