我目前正在尝试学习LSTM算法(机器学习),并试图“重塑”我的(NumPy)X测试数据数组。但是,我认为我对数组的大小似乎有疑问!
注意:我已经看过问题reshaping of an nparray returned "IndexError: tuple index out of range" 我确实了解,但是我不能将其应用于我的特定情况。
inputs = new_data[len(new_data) - len(valid) - 60:].values
inputs = inputs.reshape(-1,1)
inputs = scaler.transform(inputs)
X_test = []
for i in range(60,inputs.shape[0]):
X_test.append(inputs[i-60:i,0])
X_test = np.array(X_test)
#problem starts here:
X_test = np.reshape(X_test, (X_test.shape[0],X_test.shape[1],1))
scores = model.predict(X_test)
scores = scaler.inverse_transform(scores)
我得到的错误:
IndexError Traceback (most recent call last)
<ipython-input-28-ac22155ae52a> in <module>
----> 1 X_test = np.reshape(X_test, (X_test.shape[0],X_test.shape[1],1))
2 scores = model.predict(X_test)
3 scores = scaler.inverse_transform(scores)
IndexError: tuple index out of range
任何指针都很棒。注意:数据集由一个带有日期列和分数列的Excel文件组成。