We'll probably need the opinion of someone more knowledgeable about the
inheritance hierarchy...


On Thu, Apr 18, 2013 at 5:33 PM, Qiang Luo <notifications@github.com> wrote:

> In sklearn/linear_model/base.py:
>
> > +    """
> > +    def decision_function(self,X):
> > +        """Predict using the linear model
> > +
> > +        Parameters
> > +        ----------
> > +        X : {array-like, sparse matrix}, shape = [n_samples, n_features]
> > +
> > +        Returns
> > +        -------
> > +        array, shape = [n_samples]
> > +           Predicted target values per element in X.
> > +        """
> > +        X = atleast2d_or_csr(X)
> > +        scores = safe_sparse_dot(X, self.coef_.T, dense_output=True) + self.intercept_
> > +        return scores.ravel()
>
> Maybe LinearModel should inherits from LinearRegressorMixin
>
> —
> Reply to this email directly or view it on GitHub<https://github.com/scikit-learn/scikit-learn/pull/1867/files#r3848241>
> .
>