# torchfm.dataset

## torchfm.dataset.avazu

class `torchfm.dataset.avazu.``AvazuDataset`(dataset_path=None, cache_path='.avazu', rebuild_cache=False, min_threshold=4)

  Avazu Click-Through Rate Prediction Dataset

  Dataset preparation

    Remove the infrequent features (appearing in less than threshold instances) and treat them as a single feature

  Parameters

    - dataset_path – avazu train path

    - cache_path – lmdb cache path

    - rebuild_cache – If True, lmdb cache is refreshed

    - min_threshold – infrequent feature threshold

  Reference

    https://www.kaggle.com/c/avazu-ctr-prediction

## torchfm.dataset.criteo

class `torchfm.dataset.criteo.``CriteoDataset`(dataset_path=None, cache_path='.criteo', rebuild_cache=False, min_threshold=10)

  Criteo Display Advertising Challenge Dataset

  Data prepration:

    - Remove the infrequent features (appearing in less than threshold instances) and treat them as a single feature

    - Discretize numerical values by log2 transformation which is proposed by the winner of Criteo Competition

  Parameters

    - dataset_path – criteo train.txt path.

    - cache_path – lmdb cache path.

    - rebuild_cache – If True, lmdb cache is refreshed.

    - min_threshold – infrequent feature threshold.

  Reference:

    https://labs.criteo.com/2014/02/kaggle-display-advertising-challenge-dataset https://www.csie.ntu.edu.tw/~r01922136/kaggle-2014-criteo.pdf

## torchfm.dataset.movielens

class `torchfm.dataset.movielens.``MovieLens1MDataset`(dataset_path)

  MovieLens 1M Dataset

  Data preparation

    treat samples with a rating less than 3 as negative samples

  Parameters

    dataset_path – MovieLens dataset path

  Reference:

    https://grouplens.org/datasets/movielens

class `torchfm.dataset.movielens.``MovieLens20MDataset`(dataset_path, sep=', ')

  MovieLens 20M Dataset

  Data preparation

    treat samples with a rating less than 3 as negative samples

  Parameters

    dataset_path – MovieLens dataset path

  Reference:

    https://grouplens.org/datasets/movielens