User Guide

• Introduction
  • Design of the API
  • Which algorithms are implemented in biquality-learn ?
  • Training Biquality Learning Classifiers
  • scikit-learn’s metadata routing
  • Cross-Validating Biquality Classifiers
• Transfer Learning
  • Inductive Transfer Learning
  • Supervised Domain Adaptation
  • K-Domain Adaptation
• Radon-Nikodym Derivative
  • Importance Reweighting for Biquality Learning
  • K-Density Ratio
  • Loss based Density Ratio
• Noise Transition Matrices
  • Correcting Classifiers with Transition Matrices.
  • Estimating Noise Transition Matrices
• Simulating Corruptions
  • Biquality Data
  • Corruption API