RBFTrainer.py 文件源码

def grid_retrain_in_x(self):
        gamma_range = np.logspace(-15, 3, 19, base=2)
        param_grid = dict(gamma=gamma_range)

        if len(np.unique(self.y_ex)) < 2:
            return 1, 1

        try:
            cv = StratifiedShuffleSplit(self.y_ex, n_iter=5, test_size=.2)
            grid = GridSearchCV(SVC(C=1e5), param_grid=param_grid, cv=cv, n_jobs=-1)

            grid.fit(self.X_ex, self.y_ex)
            rbf_svc2 = grid.best_estimator_
        except ValueError:
            rbf_svc2 = SVC(C=1e5)
            rbf_svc2.fit(self.X_ex, self.y_ex)

        self.set_clf2(rbf_svc2)
        return self.benchmark()