Moffran / calibrated_explanationsLinks
Repository for the explanation method Calibrated Explanations (CE)
β70Updated last week
Alternatives and similar repositories for calibrated_explanations
Users that are interested in calibrated_explanations are comparing it to the libraries listed below
Sorting:
- π Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecasterβ115Updated 2 months ago
- Python implementation of binary and multi-class Venn-ABERS calibrationβ191Updated 2 months ago
- β115Updated last year
- β41Updated 11 months ago
- Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.β227Updated last year
- Quantile Regression Forests compatible with scikit-learn.β251Updated this week
- A Library for Conformal Hyperparameter Tuningβ104Updated 3 weeks ago
- π Puncc is a python library for predictive uncertainty quantification using conformal prediction.β365Updated 2 weeks ago
- Conformal Anomaly Detectionβ51Updated this week
- Multi-class probabilistic classification using inductive and cross VennβAbers predictorsβ50Updated 3 years ago
- Integrated tool for model development and validationβ33Updated last month
- Conformal Prediction-Based Global and Model Agnostic Explainability for Classification tasks.β26Updated 10 months ago
- β50Updated 2 months ago
- Fast implementation of Venn-ABERS probabilistic predictorsβ75Updated last year
- Practical Guide to Applied Conformal Prediction, published by Packtβ193Updated last month
- Extension of crepes package, to enable weighted conformal prediction and conformal predictive systems that can handle covariate shifts.β23Updated 10 months ago
- Methods for online conformal prediction.β117Updated 7 months ago
- Lightweight Python package for generating classification intervals in binary classification tasks using Pearson residuals and conformal pβ¦β23Updated 6 months ago
- A framework for calibration measurement of binary probabilistic modelsβ29Updated last year
- WarpGBM: High-Speed Gradient Boostingβ94Updated last month
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for anyβ¦β102Updated 3 years ago
- A simple and fast sklearn-compatible conformal predictions with random forests for both classification and regression tasks.β44Updated 4 months ago
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"β45Updated 2 years ago
- A power-full Shapley feature selection method.β211Updated 2 months ago
- A python package for time series forecasting with scikit-learn estimators.β163Updated last year
- WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)β159Updated 3 years ago
- The Orange Book of Machine Learningβ52Updated 3 months ago
- Python package for conformal predictionβ548Updated 2 months ago
- Effector - a Python package for global and regional effect methodsβ117Updated 2 weeks ago
- Helper functions to plot, evaluate, preprocess and engineer features for forecastingβ94Updated last week