def _set_intercept(self, X_offset, y_offset, X_scale):
        if self.fit_intercept:
            self.coef_ = self.coef_ / X_scale
            self.intercept_ = y_offset - np.dot(X_offset, self.coef_.T)
        else:
            self.intercept_ = 0.


# XXX Should this derive from LinearModel? It should be a mixin, not an ABC.
# Maybe the n_features checking can be moved to LinearModel.
Validate ByteString property.
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/linear_model/base.py/LinearModel._set_intercept--crossover with--dataset/ETHPy150Open AppScale/appscale/AppServer/google/appengine/ext/db/__init__.py/ByteStringProperty.validate