Quick start

Install

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Usage

To run cross-validation:

  1. Download a dataset like Movielens 100k

  2. Ensure the columns are named user,item,rating:

user

item

rating

3

5

4.5

For example, here, user 3 gave 4.5 stars to item 5.

  1. Then run:

    python compare.py <path/to/dataset>

You can tweak the experiments/default.json file to compare other models.

Custom usage

Most models have the following routines:

from zero.als import MangakiALS
model = MangakiALS(nb_components=10)
model.fit(X, y)
model.predict(X)

where:

  • X is a numpy array of size nb_samples x 2 (first column: user ID, second column: item ID)

  • and y is the column of ratings.

There are a couple of other methods that can be used for online fit, say model.predict_single_user(work_ids, user_parameters).

See zero.py as an example of dumb baseline (only predicts zeroes) to start from. See svd2.py for a more advanced example.

Results

Mangaki data

Comparing on Mangaki

Movielens data

Comparing on Movielens

Feel free to use. Under MIT license.