py-v0.3.0

Changes

Support negative down sampling rate with argument

ffm.train method now provides nds_rate argument for negative down sampling.
default nds_rate is 1.0.

Add best_va_loss to field

best_va_loss added to field for hyperparameter tuning.

import ffm

def main():
    # Prepare the data. (field, index, value) format
    X_train = [[(1, 2, 1), (2, 3, 1), (3, 5, 1)],
         [(1, 0, 1), (2, 3, 1), (3, 7, 1)],
         [(1, 1, 1), (2, 3, 1), (3, 7, 1), (3, 9, 1)], ]
    y_train = [1, 1, 0]
    X_valid = [[(1, 2, 1), (2, 3, 1), (3, 5, 1)],
         [(1, 0, 1), (2, 3, 1), (3, 7, 1)],
         [(1, 1, 1), (2, 3, 1), (3, 7, 1), (3, 9, 1)], ]
    y_valid = [1, 0, 0]
    train_data = ffm.Dataset(X_train, y_train)
    valid_data = ffm.Dataset(X_valid, y_valid)
    model = ffm.train(train_data, valid_data, quiet=False, nds_rate=0.5)

    va_logloss = model.best_va_loss
    with open("./model/prod-cvr.model", 'w') as f:
        model.dump_model(f)

if __name__ == '__main__':
    main()

Installation

from source code

$ pip install numpy Cython==3.0a6
$ pip install "git+https://github.com/CyberAgent/libffm.git@py-v0.3.0"

from sdist (source package)

$ pip install numpy
$ pip install https://github.com/CyberAgent/libffm/releases/download/py-v0.3.0/ffm-0.3.0.tar.gz