neural nets XOR

9_neural_nets-4-xor.py

+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(100, 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,  batch_size=1, nb_epoch=1000)
+print(model.predict_proba(X))