searchers.py 文件源码

def refit_model(self):
        """Learns a new surrogate model using the data observed so far.

        """

        # only fit the model if there is data for it.
        if len(self.known_models) > 0:

            self._build_feature_maps(self.known_models, self.ngram_maxlen, self.thres)

            X = sp.vstack([ self._compute_features(mdl)
                    for mdl in self.known_models], "csr")
            y = np.array(self.known_scores, dtype='float64')

            #A = np.dot(X.T, X) + lamb * np.eye(X.shape[1])
            #b = np.dot(X.T, y)
            self.surr_model = lm.Ridge(self.lamb_ridge)
            self.surr_model.fit(X, y)


# NOTE: if the search space has holes, it break. needs try/except module.