kaggle_titanic.py 文件源码

def get_sample(self, N=600, scale=False):
        all_data = self.pre_process(self.file_name)
        #print('data_type: ' + str(all_data.dtypes))
        all_data = all_data.values
        xs = all_data[:, 2:]
        y = all_data[:, 1]
        if scale:
            xs = preprocessing.scale(xs)
        if N != -1:
            perm = np.random.permutation(xs.shape[0])
            xs = xs[perm]
            y = y[perm]
            xs_train, xs_test = np.split(xs, [N])
            y_train, y_test = np.split(y, [N])
            return xs_train, xs_test, y_train, y_test
        else:
            return xs, y