使用scaler.transform重塑数据时出错

Question

我正在尝试理解并运行此code。错误是尝试通过使用scaler.transform转换为数组来重塑测试数据时。

train_data = train_data.reshape(-1)
test_data = scaler.transform(test_data).reshape(-1)   #error!

输出错误消息：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-55-c702803dbbe6> in <module>
     11 # Normalize test data
---> 13 test_data = scaler.transform(test_data).reshape(-1)

~/StockPrediction/predictionLSTM/pro1/lib/python3.7/site-packages/sklearn/preprocessing/_data.py in transform(self, X)
    406 
    407         X = check_array(X, copy=self.copy, dtype=FLOAT_DTYPES,
--> 408                         force_all_finite="allow-nan")
    409 
    410         X *= self.scale_

~/StockPrediction/predictionLSTM/pro1/lib/python3.7/site-packages/sklearn/utils/validation.py in inner_f(*args, **kwargs)
     70                           FutureWarning)
     71         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
---> 72         return f(**kwargs)
     73     return inner_f
     74 

~/StockPrediction/predictionLSTM/pro1/lib/python3.7/site-packages/sklearn/utils/validation.py in check_array(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator)
    651                              " minimum of %d is required%s."
    652                              % (n_samples, array.shape, ensure_min_samples,
--> 653                                 context))
    654 
    655     if ensure_min_features > 0 and array.ndim == 2:

ValueError: Found array with 0 sample(s) (shape=(0, 1)) while a minimum of 1 is required.

如何解决？