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epochs=5
batch_size=5
np.random.seed(1)
epochs=5
batch_size=5
np.random.seed(7820)
gap-filling with mean values.
epochs=20
batch_size=5
np.random.seed(7820)
from keras.models import Sequential
from keras.layers import Dense
classifier = Sequential()
classifier.add(Dense(units = 13, activation = 'relu'))
classifier.add(Dense(units = 1, activation = 'sigmoid'))
classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
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