Matrix Factorization: initial values

The initial distribution of feature values affects the results of matrix factorization (SVD) algorithm (this implementation). In this post, let's have a look at performance of SVD algorithm with different distributions of initial values. To conduct experiments, I used Lenskit framework and MovieLens100K dataset. The experiments includes three distributions:

1. Fixed values (0.1) (Fixed)
2. Random values (Random)
3. Popularity distribution for item features and random for user features (POP)