Answers for "how to use keras model with sklearn"

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how to use keras model with sklearn

from keras.models import Sequential
from keras.layers import Dense
from keras.wrappers.scikit_learn import KerasClassifier

# Function to create model, required for KerasClassifier
def create_model():
	# create model
	model = Sequential()
	model.add(Dense(12, input_dim=8, activation='relu'))
	model.add(Dense(8, init='normal', activation='relu'))
	model.add(Dense(1, init='normal', activation='sigmoid'))
	# Compile model
	model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
	return model

# create model
model = KerasClassifier(build_fn=create_model, nb_epoch=100, batch_size=5, verbose=0)

# now you can do fit and predict 
model.fit(x, y)
y_pred = model.predict(test)
Posted by: Guest on October-23-2021

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