def fit(self, X, y, init_weights=True):
        self._is_fitted = False
        if not (init_weights is None or isinstance(init_weights, bool)):
            raise AttributeError("init_weights must be True or False")
        self._check_arrays(X=X, y=y)
        if self.random_seed:
            np.random.seed(self.random_seed)
        self._fit(X=X, y=y, init_weights=init_weights)
        self._is_fitted = True
        return self
Learn weight coefficients from training data.
dataset/ETHPy150Open rasbt/mlxtend/mlxtend/tf_regressor/tf_linear_regression.py/TfLinearRegression.fit