Welcome to bipartite_learn’s documentation!

Contents

• User guide
  • Bipartite machine learning tasks
    • Sometimes we have two X matrices to work with
    • Bipartite estimators
    • Adapting monopartite estimators to bipartite datasets
      • The global single-output approach
      • The local multi-output approach
      • Transformers and samplers
    • Native bipartite models
  • Model validation
    • Cross-validation and hyperparameter search
    • Pipelines
• API
  • bipartite_learn
    • bipartite_learn.base
    • bipartite_learn.datasets
      • bipartite_learn.datasets.base
      • bipartite_learn.datasets.loader
    • bipartite_learn.ensemble
    • bipartite_learn.matrix_factorization
    • bipartite_learn.melter
    • bipartite_learn.metrics
    • bipartite_learn.model_selection
    • bipartite_learn.neighbors
    • bipartite_learn.pipeline
    • bipartite_learn.preprocessing
      • bipartite_learn.preprocessing.monopartite
      • bipartite_learn.preprocessing.multipartite
    • bipartite_learn.tree
    • bipartite_learn.utils
      • bipartite_learn.utils.discovery
    • bipartite_learn.wrappers