Awesome ML Positive Unlabeled learning
Papers
- Papers \w code
- Overview
- Cost-sensitive methods
- Learning Classifiers from Only Positive and Unlabeled Data(2008)[pulearn]
- Analysis of Learning from Positive and Unlabeled Data(2014)
- A Modified Logistic Regression for Positive and Unlabeled Learning(2019) [video]
- DEDPUL: Difference-of-Estimated-Densities-based Positive-Unlabeled Learning(2019)[source]
- Sample-selection/Two-step methods
- Positive-unlabeled learning for disease gene identification(2012)
- A bagging SVM to learn from positive and unlabeled examples(2013) [pulearn]
- Revisiting Sample Selection Approach to Positive-Unlabeled Learning: Turning Unlabeled Data into Positive rather than Negative(2019)
- Improving Positive Unlabeled Learning: Practical AUL Estimation and New Training Method for Extremely Imbalanced Data Sets(2020)
- PULNS: Positive-Unlabeled Learning with Effective Negative Sample Selector(2021)[slides]
Implementations
Tutorials
- An introductory tutorial to the "Learning from Positive and Unlabeled Data" field.
- tinyML Talks Phoenix: Positive Unlabeled Learning for Tiny ML
- Semi-Supervised Classification of Unlabeled Data (PU Learning)
Concepts
- Class prior and label frequency
- Cost-sensitive and sample-selection methods
- Inductive vs Transductive PU learning. a.k.a(?) (Single-training set vs case-control scenario)
- Labelling mechanism
- Assumptions