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from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import StratifiedKFold
from sklearn.model_selection import cross_val_score
import numpy
#Function to create model, required for KerasClassifier
def create_model():
classifier = Sequential()
classifier.add(Dense(12, input_dim=8, activation='relu'))
classifier.add(Dense(8, activation='relu'))
classifier.add(Dense(1, activation='sigmoid'))
classifier.compile(optimizer = 'adam',loss="mean_squared_error")
return model
seed = 7
numpy.random.seed(seed)
model = KerasClassifier(build_fn=create_model, epochs=100, batch_size=32, verbose=0)
kfold = StratifiedKFold(n_splits=10, shuffle=True, random_state=seed)
results = cross_val_score(model, X_train, y_train, cv=kfold)
print(results.mean())
AttributeError的交叉驗證:「KerasClassifier」對象有沒有屬性「損失」如何申請鉀對迴歸類型的目標變量
I am getting an error as the loss does not belong to kerasClassifier and I tried KerasRegressor also still same error I am getting.solve my issue.
是的,我糾正了它,但仍然顯示一些錯誤 –
這個錯誤是否與'AttributeError:'KerasClassifier'對象沒有屬性'損失''一樣嗎?如果你有不同的錯誤,你可以接受這個答案,並在SO上提出另一個新錯誤的問題。 –