预期的二维数组，得到一维数组

Question

我正在从 github 运行以下代码，但出现错误。怎么了？

https://github.com/susanli2016/Machine-Learning-with-Python/blob/master/Time%20Series%20ANN%20%26%20LSTM%20VIX.ipynb

细胞：

# scale train and test data to [-1, 1]

scaler = MinMaxScaler(feature_range=(-1, 1))

train_sc = scaler.fit_transform(train)

test_sc = scaler.transform(test)

错误：

ValueError: Expected 2D array, got 1D array instead:

array=[17.24     18.190001 19.219999 ... 10.47     10.18     11.04    ].

Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.

Answer 1

制作那个笔记本的人使用的是一个非常旧版本的sklearn. 简而言之，您的特征具有形式[row_1, row_2...row_n]，而它们本应具有形式[[row_1], [row_2]...[row_n]]。因此，使用这个：new_shape = (len(train), 1)train_sc = scaler.fit_transform(np.reshape(train, new_shape))test_sc = scaler.transform(np.reshape(test, new_shape))

Answer 2

解决了添加以下方法的问题，这些方法显然将训练和测试对象转换为 numpy 数组。那是对的吗？scaler = MinMaxScaler(feature_range=(-1, 1))train_sc = scaler.fit_transform(train.values.reshape(-1, 1))test_sc = scaler.transform(test.values.reshape(-1,1))