Carlos-Francisco Méndez-Cruz / lcg-bioinfoI-bionlp

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Carlos-Francisco Méndez-Cruz
f18f366c 1 parent e9b4885b

Training, crossvalidation and testing dataset

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Showing 1 changed file with 1 additions and 5 deletions
...@@ -210,15 +210,14 @@ if __name__ == "__main__": ...@@ -210,15 +210,14 @@ if __name__ == "__main__":
210 print(" Done!") 210 print(" Done!")
211 211
212 y_pred = myClassifier.predict(X_test) 212 y_pred = myClassifier.predict(X_test)
213 - best_parameters = myClassifier.best_estimator_.get_params()
214 print(" Done!") 213 print(" Done!")
215 214
216 print("Saving report...") 215 print("Saving report...")
217 with open(os.path.join(args.outputReportPath, args.outputReportFile), mode='w', encoding='utf8') as oFile: 216 with open(os.path.join(args.outputReportPath, args.outputReportFile), mode='w', encoding='utf8') as oFile:
218 oFile.write('********** EVALUATION REPORT **********\n') 217 oFile.write('********** EVALUATION REPORT **********\n')
219 - oFile.write('Reduction: {}\n'.format(args.reduction))
220 oFile.write('Classifier: {}\n'.format(args.myClassifier)) 218 oFile.write('Classifier: {}\n'.format(args.myClassifier))
221 oFile.write('Kernel: {}\n'.format(args.kernel)) 219 oFile.write('Kernel: {}\n'.format(args.kernel))
220 + oFile.write('Training score: {}\n'.format(myClassifier.score()))
222 oFile.write('Accuracy: {}\n'.format(accuracy_score(y_test, y_pred))) 221 oFile.write('Accuracy: {}\n'.format(accuracy_score(y_test, y_pred)))
223 oFile.write('Precision: {}\n'.format(precision_score(y_test, y_pred, average='weighted'))) 222 oFile.write('Precision: {}\n'.format(precision_score(y_test, y_pred, average='weighted')))
224 oFile.write('Recall: {}\n'.format(recall_score(y_test, y_pred, average='weighted'))) 223 oFile.write('Recall: {}\n'.format(recall_score(y_test, y_pred, average='weighted')))
...@@ -227,9 +226,6 @@ if __name__ == "__main__": ...@@ -227,9 +226,6 @@ if __name__ == "__main__":
227 oFile.write(str(confusion_matrix(y_test, y_pred)) + '\n') 226 oFile.write(str(confusion_matrix(y_test, y_pred)) + '\n')
228 oFile.write('Classification report: \n') 227 oFile.write('Classification report: \n')
229 oFile.write(classification_report(y_test, y_pred) + '\n') 228 oFile.write(classification_report(y_test, y_pred) + '\n')
230 - oFile.write('Best parameters: \n')
231 - for param in sorted(best_parameters.keys()):
232 - oFile.write("\t%s: %r\n" % (param, best_parameters[param]))
233 print(" Done!") 229 print(" Done!")
234 230
235 print("Training and testing done in: %fs" % (time() - t0)) 231 print("Training and testing done in: %fs" % (time() - t0))
......