noislearn¶

noislearn is an scikit-learn compatible toolkit for label-noise filtering, iterative cleaning, and explainable inspection of noisy decisions.

Distance-based filters Classifier-based filters TabPFN explanations CNC-NOS cleaner

:material-filter: Filters

Classical, distance-based, ensemble-based, and TabPFN-based noise filters.

Browse the filters
:material-broom: Cleaners

Higher-level cleaning pipelines built on top of the available filters.

Open the cleaners API
:material-book-open-page-variant: Concepts

Short guides on noise models, filtering strategies, and local explanations.

Read the guides
:material-chart-box-outline: TabPFN explainability

Local SHAP-based reports for noisy-instance inspection and auditability.

Explore the explanation model

Note

The API pages are generated from the public docstrings in the source tree.