\n
\n "},"metadata":{},"execution_count":5}],"execution_count":5},{"cell_type":"code","source":"y","metadata":{"id":"xgSeoBePOTzL","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"f3cad5aa597d482dae2fda8646dc491b","outputId":"9ff83f30-9637-4205-cd83-7126acc18c86","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":4,"user_tz":240,"timestamp":1650987598263},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"0 0\n1 0\n2 0\n3 0\n4 0\n ..\n195 1\n196 1\n197 1\n198 1\n199 1\nName: y, Length: 200, dtype: int64"},"metadata":{},"execution_count":6}],"execution_count":6},{"cell_type":"code","source":"X_train, X_test, y_train, y_test = train_test_split(X,y.values.reshape(-1,1),train_size= 0.7,random_state = 42,shuffle=True)","metadata":{"id":"9PZ3r3zLORPV","cell_id":"2f1371718ed640be9d20ba5c877ea4d6","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":5,"user_tz":240,"timestamp":1650987599646},"deepnote_cell_type":"code"},"outputs":[],"execution_count":7},{"cell_type":"code","source":"# Creación del modelo SVM \nmodelo = SVC(C = 100, kernel = 'linear', random_state=42)\nmodelo.fit(X_train, y_train)","metadata":{"id":"TfGGYtOvaGjm","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"642570b494bd494c8db0e2501374202d","outputId":"933e3df6-796e-4a84-8c4b-350f6f5df8e4","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":514,"user_tz":240,"timestamp":1650987600158},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"SVC(C=100, kernel='linear', random_state=42)"},"metadata":{},"execution_count":8}],"execution_count":8},{"cell_type":"code","source":"#Predicciones!\ny_test_pred = modelo.predict(X_test)","metadata":{"id":"U4zcXt7faGjn","cell_id":"f8a6de7201144d08bf170d3e51b1c731","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":9,"user_tz":240,"timestamp":1650987601361},"deepnote_cell_type":"code"},"outputs":[],"execution_count":9},{"cell_type":"markdown","source":"A lo largo de este notebook, se solicita calcular las métricas requeridas como así también su correspondiente interpretación: \n\n1. Calcular la métrica Accuracy.","metadata":{"id":"4o1E5zjBaGjp","cell_id":"6add817297844637bfa00f090504f2d6","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"###Completar\nfrom sklearn.metrics import accuracy_score\naccuracy_score(y_test,y_test_pred)","metadata":{"id":"vUSJj6eMaGjt","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"6e36e02bc3f3476db650f03b48246140","outputId":"959ae872-5127-4fab-e1e8-5ff577cafb56","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":453,"user_tz":240,"timestamp":1650987602244},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"0.7"},"metadata":{},"execution_count":10}],"execution_count":10},{"cell_type":"markdown","source":"2. Crear la Matriz de Confusión","metadata":{"id":"an4bC4jIaGjv","cell_id":"180733fc43fe402e9b76da28e7ea17a6","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"###Completar\nfrom sklearn.metrics import confusion_matrix\nconfusion_matrix(y_test, y_test_pred) ","metadata":{"id":"55vncdmWaGjx","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"67364bbd50a24936a1deb4cfd838065d","outputId":"9f294484-1b6c-44ad-a3e3-0426fcd82e7f","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":5,"user_tz":240,"timestamp":1650987602628},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"array([[21, 10],\n [ 8, 21]])"},"metadata":{},"execution_count":11}],"execution_count":11},{"cell_type":"markdown","source":"3. Calcular la métrica F1 score","metadata":{"id":"NUeSPxVhaGjy","cell_id":"d436803a5e7341ab8b2f8c4e5f193541","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"###Completar\nfrom sklearn.metrics import f1_score\nf1_score(y_test, y_test_pred) ","metadata":{"id":"BmppWOhdaGjz","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"0bf9f56784d74f59b029859decf1b71f","outputId":"c8ab8479-c67e-4a49-ed57-37b3622917d4","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":7,"user_tz":240,"timestamp":1650987603714},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"0.7"},"metadata":{},"execution_count":12}],"execution_count":12},{"cell_type":"markdown","source":"Calcular todas las metricas al tiempo","metadata":{"id":"zTgUTEomPquo","cell_id":"ed261c673aa741ce993425bc808244f3","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"from sklearn.metrics import classification_report\nreporte=classification_report(y_test,y_test_pred)\nprint(reporte)","metadata":{"id":"aqPX-U4VPhnY","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"82a0744a1498495384a4bcbef798f18a","outputId":"6d34d466-7ce2-4bee-b7ca-69fd2a4018e4","executionInfo":{"user":{"userId":"09471607480253994520","displayName":"David Francisco Bustos Usta"},"status":"ok","elapsed":4,"user_tz":240,"timestamp":1650987605214},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":" precision recall f1-score support\n\n 0 0.72 0.68 0.70 31\n 1 0.68 0.72 0.70 29\n\n accuracy 0.70 60\n macro avg 0.70 0.70 0.70 60\nweighted avg 0.70 0.70 0.70 60\n\n"}],"execution_count":13},{"cell_type":"markdown","source":"\n\n
\n \n\n\n \n
\n
\n \n \n \n\n \n | \n | X1 | \nX2 | \n
|---|---|---|
| 0 | \n2.526093 | \n0.321050 | \n
| 1 | \n0.366954 | \n0.031462 | \n
| 2 | \n0.768219 | \n0.717486 | \n
| 3 | \n0.693436 | \n0.777194 | \n
| 4 | \n-0.019837 | \n0.867254 | \n
| ... | \n... | \n... | \n
| 195 | \n0.256750 | \n2.293605 | \n
| 196 | \n1.925173 | \n0.165053 | \n
| 197 | \n1.301941 | \n0.992200 | \n
| 198 | \n0.008131 | \n2.242264 | \n
| 199 | \n-0.196246 | \n0.551404 | \n
200 rows × 2 columns
\n
\nCreated in Deepnote","metadata":{"created_in_deepnote_cell":true,"deepnote_cell_type":"markdown"}}],"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"SVM (Ejemplo 3 - Alumnos).ipynb","provenance":[],"collapsed_sections":[]},"deepnote":{},"kernelspec":{"name":"python3","language":"python","display_name":"Python 3"},"varInspector":{"cols":{"lenVar":40,"lenName":16,"lenType":16},"kernels_config":{"r":{"library":"var_list.r","varRefreshCmd":"cat(var_dic_list()) ","delete_cmd_prefix":"rm(","delete_cmd_postfix":") "},"python":{"library":"var_list.py","varRefreshCmd":"print(var_dic_list())","delete_cmd_prefix":"del ","delete_cmd_postfix":""}},"window_display":false,"types_to_exclude":["module","function","builtin_function_or_method","instance","_Feature"]},"language_info":{"name":"python","version":"3.8.5","mimetype":"text/x-python","file_extension":".py","pygments_lexer":"ipython3","codemirror_mode":{"name":"ipython","version":3},"nbconvert_exporter":"python"},"deepnote_notebook_id":"d86e78ee518e49069d2bf9003d0cd7d6","deepnote_execution_queue":[]}}