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API Reference

This section contains the auto-generated API documentation for WarpRec's core components. Each page provides class signatures, parameters, attributes, and source code for the corresponding module.

Data

  • Dataset -- Dataset and evaluation dataloaders.
  • Entities -- Interaction, Session and training dataloaders.
  • Filtering -- Filter.
  • Reader -- Reader, ReaderFactory and Reader implementations.
  • Splitting -- Splitter and SplittingStrategies.
  • Writer -- Writer, WriterFactory and Writer implementations.

Recommenders

  • Model Interfaces -- Model interfaces and Mixin classes.
  • Collaborative Filtering -- Autoencoder, Graph-Based, KNN, Latent Factor, and Neural models.
  • Content-Based -- Vector Space Model and content-based approaches.
  • Hybrid -- Hybrid autoencoder and KNN models.
  • Context-Aware -- Factorization Machine variants and deep context models.
  • Sequential -- CNN, RNN, Markov, and Transformer-based sequential models.
  • Unpersonalized -- Popularity and Random baselines.
  • Proxy -- Proxy Recommender for cross-framework evaluation.

Metrics

  • Metric Interfaces -- Metric interfaces and utility classes.
  • Accuracy -- AUC, F1, GAUC, HitRate, LAUC, MAP, MAR, MRR, nDCG, Precision, Recall.
  • Bias -- ACLT, APLT, ARP, PopREO, PopRSP.
  • Coverage -- ItemCoverage, UserCoverage, NumRetrieved, UserCoverageAtN.
  • Diversity -- Gini, ShannonEntropy, SRecall.
  • Fairness -- BiasDisparity, ItemMAD, REO, RSP, UserMAD.
  • Novelty -- EFD, EPC.
  • Rating -- MAE, MSE, RMSE.
  • Multiobjective -- EucDistance, Hypervolume.