word2vec.py 文件源码

def fit(self, X_raw, y=None):
        cents = self.vect.fit_transform(X_raw)
        # print("Largest singular value: {:.2f}".format(
        #     np.linalg.norm(cents, ord=2)))
        # cents = all_but_the_top(cents, 1)
        # print("Largest singular value: {:.2f}".format(
        #     np.linalg.norm(cents, ord=2)))
        # print("Renormalizing")
        # normalize(cents, copy=False)
        # print("Largest singular value: {:.2f}".format(
        #     np.linalg.norm(cents, ord=2)))
        self.centroids = cents
        print(' FIT centroids shape', self.centroids.shape)

        self._y = y
        if self.matching:
            self.matching.fit(X_raw)
        else:
            self.nn.fit(cents)