Question

好的，从顶部开始，这是我使用的导入

import keras
from keras import layers
from keras.models import Sequential
import pandas as pd
from sklearn.model_selection import train_test_split

然后我使用熊猫从csv获取数据，然后将必要的字段分为X和y，还将其分为训练和测试集。

df = pd.read_csv('data/BCHAIN-NEW.csv')
y = df['Predict']
X = df[['Value USD', 'Drop 7', 'Up 7', 'Mean Change 7', 'Change']]

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, shuffle=False)

这没有改组，因此数据被平均分割

X_test.head()
>>>
        Value USD   Drop 7  Up 7    Mean Change 7   Change
2320    1023.14     5.0     2.0     -22.754286      -103.62
2321    1126.76     5.0     2.0     -4.470000       132.09
2322    994.67      5.0     2.0     9.865714        111.58
2323    883.09      5.0     2.0     9.005714        -13.74
2324    896.83      5.0     2.0     12.797143       -11.31

X_train.head()
>>>
    Value USD   Drop 7  Up 7    Mean Change 7   Change
0   0.06480     2.0     4.0     -0.000429       -0.00420
1   0.06900     1.0     5.0     0.000274        0.00403
2   0.06497     1.0     5.0     0.000229        0.00007
3   0.06490     1.0     5.0     0.000514        0.00200
4   0.06290     2.0     4.0     0.000229        -0.00050

现在像这样运行模型会引发索引错误

model = Sequential()
model.add(layers.Dense(100, activation='relu', input_shape=(5,)))
model.add(layers.Dense(100, activation='relu'))
model.add(layers.Dense(5, activation='softmax'))
model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
model.fit(X_train, y_train, epochs=3)

>>>
Epoch 1/3

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-38-868bc86350df> in <module>()
      4 model.add(layers.Dense(5, activation='softmax'))
      5 model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy'])
----> 6 model.fit(X_train, y_train, epochs=3)

c:\users\samuel\appdata\local\programs\python\python35\lib\site-packages\keras\models.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, **kwargs)

...

c:\users\samuel\appdata\local\programs\python\python35\lib\site-packages\pandas\core\indexing.py in _convert_to_indexer(self, obj, axis, is_setter)
   1267                 if mask.any():
   1268                     raise KeyError('{mask} not in index'
-> 1269                                    .format(mask=objarr[mask]))
   1270 
   1271                 return _values_from_object(indexer)

KeyError: '[1330  480  101 2009 1131  379 1498 2188 2121  700 1877 2011 2244 1262\n 1493  956  150  479 1345 1073 1173 1909 2260 2288  355  670 2143 1426\n   42  952  358 1183] not in index'

Answer 1

在我看来，您的数据格式错误，需要使用numpy数组。（假设它们不是已经准备好的numpy数组）

尝试像这样转换它们

x_train = np.array(x_train)
y_train = np.array(y_train)

tensorflow / keras训练模型keyerror

1 个答案: