added examples
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1 changed files with 15 additions and 3 deletions
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@ -12,17 +12,29 @@ from sklearn.dummy import DummyClassifier
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X_eg = np.array([-1, 1, 1, 1])
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y_eg = np.array([0, 1, 1, 1])
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dummy_clf = DummyClassifier(strategy="most_frequent")
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dummy_clf = DummyClassifier(strategy="stratified")
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dummy_clf = DummyClassifier(strategy="stratified")
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dummy_clf.fit(X_eg, y_eg)
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DummyClassifier(strategy='most_frequent')
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#DummyClassifier(strategy='most_frequent')
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dummy_clf.predict(X_eg)
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np.array([1, 1, 1, 1])
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dummy_clf.predict(np.array([1,1,1,1,1,1,1,1,1,1]))
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dummy_clf.predict_proba(X_eg)
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dummy_clf.score(X_eg, y_eg)
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0.75
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dummy_clf.matthews_corrcoef(X_eg, y_eg)
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df2['X']
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dummy_clf.fit(df2['X'], df2['y'])
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dummy_clf.predict(df2['X'])
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dummy_clf.predict_proba(df2['X'])
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ypred = dummy_clf.predict(df2['X'])
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dummy_clf.score(df2['X'], df2['y'])
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confusion_matrix(df2['y'], ypred)
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matthews_corrcoef(df2['y'], ypred)
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#%%
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df['dst_mode']
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y_all_tt = df.loc[:,'dst']
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