#!/usr/bin/env python
# coding: utf-8

# In[44]:


from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.datasets import boston_housing


# In[45]:


(X_train, Y_train), (X_test, Y_test) = boston_housing.load_data()


# In[47]:


nFeatures = X_train.shape[1]

model = Sequential()
model.add(Dense(1, input_shape=(nFeatures,), kernel_initializer='uniform'))
model.add(Activation('linear'))

model.compile(optimizer='rmsprop',  loss='mse', metrics=['mse', 'mae'])

model.fit(X_train, Y_train, batch_size=4, epochs=1000)


# In[48]:


model.summary()

model.evaluate(X_test, Y_test, verbose=True)


# In[39]:


Y_pred = model.predict(X_test)


# In[40]:


print Y_test[:5]
print Y_pred[:5,0]