Implementing linear regression in keras

linearReg.py

"""
Author: Shubhanshu Mishra
Posted this on the keras issue tracker at: https://github.com/fchollet/keras/issues/108
Implementing a linear regression using Keras. 
"""

from keras.models import Sequential
from keras.layers.core import Dense, Activation

model = Sequential()
model.add(Dense(2,1,init='uniform', activation='linear'))
model.compile(loss='mse', optimizer='rmsprop')

model.fit(X_train, y_train, nb_epoch=1000, batch_size=16,verbose=0)
model.fit(X_train, y_train, nb_epoch=1, batch_size=16,verbose=1)
score = model.evaluate(X_test, y_test, batch_size=16)

No longer works on the latest version of Keras

@scottlawsonbc This will work if you reformat the Dense layer to the new format.

Hello, I'm knew to Keras. Can you show me how to write it with the new Dense format? Thanks!

@qks1lver it should be model.add(Dense(1, input_dim=2)) for the new api I think assuming 1 output from two input