반환값
        -------
        self : object

        """
        self._initialize_weights(X.shape[1])
        self.losses_ = []
        for i in range(self.n_iter):
            if self.shuffle:
                X, y = self._shuffle(X, y)
            losses = []
            for xi, target in zip(X, y):
                losses.append(self._update_weights(xi, target))
            avg_loss = np.mean(losses) 
            self.losses_.append(avg_loss)
        return self

    def partial_fit(self, X, y):
        """가중치를 다시 초기화하지 않고 훈련 데이터를 학습합니다"""
        if not self.w_initialized:
            self._initialize_weights(X.shape[1])
        if y.ravel().shape[0] > 1:
            for xi, target in zip(X, y):
                self._update_weights(xi, target)
        else:
            self._update_weights(X, y)
        return self