(self, X, y)
Update the model with the new additional data. Override this function if your
        model allows to do something smarter than simple retraining

        Parameters
        ----------
        X: np.ndarray (N, D)
            Input data points. The dimensionality of X is (N, D),
            with N as the number of points and D is the number of input dimensions.
        y: np.ndarray (N,)
            The corresponding target values of the input data points.
Update the model with the new additional data. Override this function if your
        model allows to do something smarter than simple retraining
Update the model with the new additional data . Override this function if your model allows to do something smarter than simple retraining
def update(self, X, y):
        """
        Update the model with the new additional data. Override this function if your
        model allows to do something smarter than simple retraining

        Parameters
        ----------
        X: np.ndarray (N, D)
            Input data points. The dimensionality of X is (N, D),
            with N as the number of points and D is the number of input dimensions.
        y: np.ndarray (N,)
            The corresponding target values of the input data points.
        """
        X = np.append(self.X, X, axis=0)
        y = np.append(self.y, y, axis=0)
        self.train(X, y)
def update ( self , X , y ) : X = np . append ( self . X , X , axis = 0 ) y = np . append ( self . y , y , axis = 0 ) self . train ( X , y )