0
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的交叉验证:“KerasClassifier”对象有没有属性“损失”如何申请钾对回归类型的目标变量
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,我纠正了它,但仍然显示一些错误 –
这个错误是否与'AttributeError:'KerasClassifier'对象没有属性'损失''一样吗?如果你有不同的错误,你可以接受这个答案,并在SO上提出另一个新错误的问题。 –