Simple XOR learning with keras

from keras.models import Sequential from keras.layers.core import Dense, Dropout, Activation from keras.optimizers import SGD import numpy as np

X = np.array([[0,0],[0,1],[1,0],[1,1]]) y = np.array([[0],[1],[1],[0]])

model = Sequential() model.add(Dense(8, input_dim=2)) model.add(Activation('tanh')) model.add(Dense(1)) model.add(Activation('sigmoid'))

sgd = SGD(lr=0.1) model.compile(loss='binary_crossentropy', optimizer=sgd)

model.fit(X, y, show_accuracy=True, batch_size=1, nb_epoch=1000) print(model.predict_proba(X)) """ [[ 0.0033028 ] [ 0.99581173] [ 0.99530098] [ 0.00564186]] """