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我試圖根據我的數據集中的部分功能來訓練Keras模型。我已經加載的數據集和提取,像這樣的特徵:熊貓 - KeyError:'[]不在索引'當培訓Keras模型
train_data = pd.read_csv('../input/data.csv')
X = train_data.iloc[:, 0:30]
Y = train_data.iloc[:,30]
# Code for selecting the important features automatically (removed) ...
# Selectintg important features 14,17,12,11,10,16,18,4,9,3
X = train_data.reindex(columns=['V14','V17','V12','V11','V10','V16','V18','V4','V9','V3'])
print(X.shape[1]) # -> 10
但是當我打電話的擬合方法:
# Fit the model
history = model.fit(X, Y, validation_split=0.33, epochs=10, batch_size=10, verbose=0, callbacks=[early_stop])
我得到以下錯誤:
KeyError: '[3 2 5 1 0 4] not in index'
我錯過了什麼?
檢查[此線程](https://stackoverflow.com/questions/33564181/keras-gru-nn-keyerror-when-fitting-not-in-index)。 –