Hi everyone,
I'm using a generalized low-rank estimator to infer missing values in a data set regarding sensor readings. I'm using H2O to create and train the model:
glrm = H2OGeneralizedLowRankEstimator(k=10,
loss="quadratic",
gamma_x=0.5,
gamma_y=0.5,
max_iterations=2000,
recover_svd=True,
init="SVD",
transform="standardize")
glrm.train(training_frame=train)
After the model is trained, the information provided regarding the performance metrics (MSE and RMSE) both return NaN. Does anybody know why? Firstly I thought it could be related to NaN entries in the data set, but I have already tried with one that is complete, and the same problem occurs.
I need this information to perform a grid search over some of the model parameters to select the best one.
Thank you very much,
Luísa Nogueira