Shortcut to `model.fit(X, y); return model.predict(X_)`.
        
        Parameters:
        -----------
        X : matrix, shape (n_samples, n_features)
        The samples, the train data.

        y : vector, shape (n_samples,)
        The target labels.

        X_ : matrix, shape (m_samples, m_features)
        The samples which labels to predict.
        
        Returns:
        --------
        y : vector, shape (m_samples,)
        The predicted labels.

def fit_predict(self, X, y, X_):
        """Shortcut to `model.fit(X, y); return model.predict(X_)`.
        
        Parameters:
        -----------
        X : matrix, shape (n_samples, n_features)
        The samples, the train data.

        y : vector, shape (n_samples,)
        The target labels.

        X_ : matrix, shape (m_samples, m_features)
        The samples which labels to predict.
        
        Returns:
        --------
        y : vector, shape (m_samples,)
        The predicted labels.
        
        """

        self.fit(X, y)
        return self.predict(X_)