def train_session(root, train, test, sideinfo=None):
import shutil
shutil.rmtree(root, ignore_errors=True)
os.makedirs(root)
print("save prefix = ", root)
trainSession = smurff.TrainSession(
num_latent=4,
burnin=800,
nsamples=100,
verbose=global_verbose,
save_freq=1,
save_prefix=root,
)
trainSession.addTrainAndTest(train, test, smurff.FixedNoise(1.0))
if sideinfo is not None:
trainSession.addSideInfo(0,
sideinfo,
smurff.FixedNoise(10.),
direct=True)
predictions = trainSession.run()
rmse = smurff.calc_rmse(predictions)
#print("RMSE = %.2f%s" % (rmse, "" if sideinfo is None else " (with sideinfo)" ))
return rmse
def noise_fixed10():
return smurff.FixedNoise(10.0)
def noise_fixed5():
return smurff.FixedNoise(5.0)
def test_fixed10(self):
self.run_session(smurff.FixedNoise(10.0))
def test_fixed5(self):
self.run_session(smurff.FixedNoise(5.0))
def get_side_noise(self):
return smurff.FixedNoise(10.)
def get_train_noise(self):
return smurff.FixedNoise(1.0)
#!/usr/bin/env python
import smurff
import pickle
Y = smurff.matrix_io.read_matrix("ratings_1k_random.sdm")
Ytrain, Ytest = smurff.prepare.make_train_test(Y, 0.2)
sideinfo = smurff.matrix_io.read_matrix("features_1k_random.sdm")
trainSession = smurff.TrainSession(num_latent=8,
burnin=200,
nsamples=200,
verbose=1,
save_name="movielens.hdf5",
save_freq=1)
trainSession.addTrainAndTest(Ytrain, Ytest)
trainSession.addSideInfo(0, sideinfo, smurff.FixedNoise(10.))
trainSession.run()