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([[1,0],[0,1],[0,1],[1,0]])

X = np.array([[0,0],[0,1],[1,0],[1,1]])
y = np.array([[0.2,0.0,0.8],[0.0,1.0,0.0],[0.15,0.25,0.6],[0.1,0.2,0.7]])

model = Sequential()
model.add(Dense(8, input_dim=2))
model.add(Activation('tanh'))
model.add(Dense(3))
model.add(Activation('softmax'))

sgd = SGD(learning_rate=0.05)
model.compile(loss='categorical_crossentropy', optimizer=sgd)

model.fit(X, y, epochs=10000)
np.set_printoptions(precision=3, suppress=True)
print(model.predict(X))
"""
[[ 0.0033028 ]
 [ 0.99581173]
 [ 0.99530098]
 [ 0.00564186]]
"""

#0.198 0.024 0.777