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features = [[300, 0,-0.05],
            [250, 2, 0.05],
            [800, 0, 0.2],
            [400, 3, 0],
            [250, 15, -0.8]]


    

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features


    

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labels = [[0],
          [0],
          [0],
          [0],
          [1]]


    

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from sklearn.linear_model import LogisticRegression


    

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model = LogisticRegression()


    

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model.fit(features, labels)


    

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model.predict([[400,16,-0.2]])


    

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model.predict_proba([[400,16,-0.2]])


    

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model.coef_


    

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