# sparse_discrete

download http://files.grouplens.org/datasets/movielens/ml-25m.zip and unzip into a folder ml-25m/

download http://files.grouplens.org/datasets/movielens/ml-1m.zip and unzip into a folder ml-1m/

run python3 movielens_data.py, which extracts the .dat files in ml-1m/ and generates ml1m_ratings.csv

by now, make sure you have ml-25m/ratings.csv and ml1m_ratings.csv

============================================================================================================================

# movielens 25 million:

## run full grid search: see generate_grid() in movielens.py

python3 movielens.py --model_path sparseMF --latent_dim 16 --lda2 0.000002 --dataset 25m

## run baselines

baseline: python3 movielens.py --model_path MF --latent_dim 16 --dataset 25m

mixed dim: python3 movielens.py --model_path mdMF --base_dim 16 --temperature 0.4 --k 8 --dataset 25m

## run Anchor & Transform

ours: python3 movielens.py --model_path sparseMF --latent_dim 16 --user_anchors 50 --item_anchors 10 --lda2 0.000002 --dataset 25m

## run Nonparametric Anchor & Transform

python3 movielens.py --model_path sparseMF --latent_dim 16 --lda1 0.01 --lda2 0.000003 --dataset 25m --dynamic
