User 3218 | 2/27/2016, 8:22:32 AM
I have a binary [thumbs-up/thumbs-down] recommender built using a factorization recommender (with side information). The distribution of thumbs-up vs. thumbs-down is 16:1. I have more than a 100M such labels. Given this skewed distribution, what are the best practices in Graphlab to deal with label imbalance problem for recommendation? I am aware of downsampling the dominant distribution using
SFrame.sample(), but writing here to see if there is a better way to deal with this.