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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def predict(self, X, cut_point=0.5):
 """Predicted class. Parameters X : array-like, shape = [n_samples, n_features] Returns ------- T : array-like, shape = [n_samples] Returns the prediction of the sample.. """

        return np.floor(self.predict_proba(X)[:, 1] + (1 - cut_point))