We do cross-validation tests to see how well the model predicts actual
behavior. As to the best data mix, cross-validation works with any engine
tuning or data input. Typically this requires re-traiing between test runs so
make sure you use exatly the same training/test split. If you want to
Hi,
With the Universal Recommender,
1. How can we validate the model after we train and deploy it?
2. How can we find an appropriate method of data mixing ??
Thanks
--
Saarthak Chandra,
Masters in Computer Science,
Cornell University.
