added main method
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@ -105,18 +105,19 @@ class DecisionTree:
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# sum(f1_scores_train)/float(len(f1_scores_train))))
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# print()
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#################################
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print('# starting decision tree')
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print('# ...')
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if __name__ == '__main__':
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file = 'classification_labelled_corrected.csv'
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print('# starting decision tree')
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print('# ...')
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# read csv file
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print('# reading dataset')
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print('# ...')
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file = 'classification_labelled_corrected.csv'
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dataset = CsvHandler.read_csv(file)
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# read csv file
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print('# reading dataset')
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print('# ...')
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make_tree(dataset)
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dataset = CsvHandler.read_csv(file)
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print('# ending decision tree')
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make_tree(dataset)
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print('# ending decision tree')
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@ -159,19 +159,20 @@ class NaiveBayes:
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#print metrics
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print('F1 score: ', format(f1_score(y_train_test, predictions)))
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#################################
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print('# starting naive bayes')
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print('# ...')
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if __name__ == '__main__':
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file = 'classification_labelled_corrected.csv'
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print('# starting naive bayes')
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print('# ...')
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# read csv file
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print('# reading dataset')
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print('# ...')
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file = 'classification_labelled_corrected.csv'
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dataset = CsvHandler.read_csv(file)
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# read csv file
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print('# reading dataset')
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print('# ...')
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make_naive_bayes(dataset)
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dataset = CsvHandler.read_csv(file)
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print('#')
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print('# ending naive bayes')
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make_naive_bayes(dataset)
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print('#')
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print('# ending naive bayes')
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@ -16,6 +16,10 @@ graphviz==0.9
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scikit_learn==0.19.2
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## Installation under (UBUNTU?)
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## Installation under Windows
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pip install XY
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## Installation under UBUNTU
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apt-get install XX
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10
Requester.py
10
Requester.py
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@ -93,8 +93,10 @@ class Requester:
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columns=['Timestamp', 'Title', 'Text', 'SiteSection'])
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# save csv
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CsvHandler.write_csv(df, filestring)
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if __name__ == '__main__':
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print('# starting requester')
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print('# ...')
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save_articles_from_webhoseio()
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print('# ending requester')
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print('# starting requester')
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print('# ...')
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save_articles_from_webhoseio()
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print('# ending requester')
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21
SVM.py
21
SVM.py
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@ -84,18 +84,19 @@ class SVM:
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print(grid.best_params_)
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print()
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########################
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print('# starting svm')
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print('# ...')
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if __name__ == '__main__':
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file = 'classification_labelled_corrected.csv'
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print('# starting svm')
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print('# ...')
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# read csv file
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print('# reading dataset')
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print('# ...')
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file = 'classification_labelled_corrected.csv'
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dataset = CsvHandler.read_csv(file)
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# read csv file
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print('# reading dataset')
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print('# ...')
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make_svm(dataset)
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dataset = CsvHandler.read_csv(file)
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print('# ending svm')
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make_svm(dataset)
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print('# ending svm')
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