from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.optimizers import SGD


model = Sequential()
model.add(Dense(output_dim=64, input_dim=100))
model.add(Activation("relu"))
model.add(Dense(output_dim=10))
model.add(Activation("softmax"))

model.compile(loss='categorical_crossentropy', optimizer='sgd', metrics=['accuracy'])
model.compile(loss='categorical_crossentropy', optimizer=SGD(lr=0.01, momentum=0.9, nesterov=True))
model.fit(X_train, Y_train, nb_epoch=5, batch_size=32)
loss_and_metrics = model.evaluate(X_test, Y_test, batch_size=32)
classes = model.predict_classes(X_test, batch_size=32)
proba = model.predict_proba(X_test, batch_size=32)

