Training, crossvalidation and testing binding thrombin dataset
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| ... | @@ -234,13 +234,17 @@ if __name__ == "__main__": | ... | @@ -234,13 +234,17 @@ if __name__ == "__main__": |
| 234 | print(" Done!") | 234 | print(" Done!") |
| 235 | 235 | ||
| 236 | print("Testing (prediction in new data)...") | 236 | print("Testing (prediction in new data)...") |
| 237 | + if args.reduction is not None: | ||
| 238 | + X_test = reduc.transform(X_test) | ||
| 237 | y_pred = classifier.predict(X_test) | 239 | y_pred = classifier.predict(X_test) |
| 238 | print(" Done!") | 240 | print(" Done!") |
| 239 | 241 | ||
| 240 | print("Saving report...") | 242 | print("Saving report...") |
| 241 | with open(os.path.join(args.outputReportPath, args.outputReportFile), mode='w', encoding='utf8') as oFile: | 243 | with open(os.path.join(args.outputReportPath, args.outputReportFile), mode='w', encoding='utf8') as oFile: |
| 242 | oFile.write('********** EVALUATION REPORT **********\n') | 244 | oFile.write('********** EVALUATION REPORT **********\n') |
| 245 | + oFile.write('Reduction: {}\n'.format(args.reduction)) | ||
| 243 | oFile.write('Classifier: {}\n'.format(args.classifier)) | 246 | oFile.write('Classifier: {}\n'.format(args.classifier)) |
| 247 | + oFile.write('Kernel: {}\n'.format(args.kernel)) | ||
| 244 | oFile.write('Accuracy: {}\n'.format(accuracy_score(y_test, y_pred))) | 248 | oFile.write('Accuracy: {}\n'.format(accuracy_score(y_test, y_pred))) |
| 245 | oFile.write('Precision: {}\n'.format(precision_score(y_test, y_pred, average='weighted'))) | 249 | oFile.write('Precision: {}\n'.format(precision_score(y_test, y_pred, average='weighted'))) |
| 246 | oFile.write('Recall: {}\n'.format(recall_score(y_test, y_pred, average='weighted'))) | 250 | oFile.write('Recall: {}\n'.format(recall_score(y_test, y_pred, average='weighted'))) | ... | ... |
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