boselector.py 文件源码

def fit_cv(self, data, labels, cv_params, epochs=10, **kwargs):

        n_jobs = kwargs.get('n_jobs', 1)
        iid = kwargs.get('iid', True)
        refit = kwargs.get('refit', True)
        cv = kwargs.get('cv', None)
        verbose = kwargs.get('verbose', 0)
        pre_dispatch = kwargs.get('pre_dispatch', '2*n_jobs')
        error_score = kwargs.get('error_score', 'raise')
        return_train_score = kwargs.get('return_train_score', True)

        param_dct = self.get_params()
        param_dct.update({'bootstrap_fraction': 1.0})

        rscv = GridSearchCV(SGDBolasso(**param_dct),
                            scoring=make_scorer(accuracy_score),
                            verbose=verbose,
                            param_grid=cv_params,
                            fit_params={'epochs': 1, 'verbose': 0},
                            cv=cv,
                            return_train_score=return_train_score,
                            n_jobs=n_jobs,
                            iid=iid,
                            refit=refit,
                            pre_dispatch=pre_dispatch,
                            error_score=error_score)

        rscv.fit(data, labels)

        param_dct = rscv.best_params_.copy()
        param_dct.update({'bootstrap_fraction': self.bootstrap_fraction})
        best_estim = SGDBolasso(**param_dct)

        best_estim.fit(data, labels, epochs=epochs)
        return best_estim, rscv