classifier-calibration / PyCalibLinks
Python library for classifier calibration
☆18Updated last year
Alternatives and similar repositories for PyCalib
Users that are interested in PyCalib are comparing it to the libraries listed below
Sorting:
- Calibration library and code for the paper: Verified Uncertainty Calibration. Ananya Kumar, Percy Liang, Tengyu Ma. NeurIPS 2019 (Spotlig…☆150Updated 2 years ago
- Model-agnostic posthoc calibration without distributional assumptions☆42Updated last year
- Reliability diagrams visualize whether a classifier model needs calibration☆154Updated 3 years ago
- Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true cla…☆244Updated 2 years ago
- ☆17Updated 4 years ago
- Conformalized Quantile Regression☆284Updated 3 years ago
- For calculating Shapley values via linear regression.☆70Updated 4 years ago
- For calculating global feature importance using Shapley values.☆274Updated this week
- [NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets☆86Updated 2 years ago
- A repo for transfer learning with deep tabular models☆104Updated 2 years ago
- An amortized approach for calculating local Shapley value explanations☆99Updated last year
- Beta calibration☆30Updated last year
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆47Updated 3 years ago
- ☆57Updated last year
- A benchmark for distribution shift in tabular data☆55Updated last year
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆43Updated 9 months ago
- Uncertainty-aware classification.☆17Updated 3 years ago
- ☆109Updated 4 years ago
- Codebase for "A Consistent and Differentiable Lp Canonical Calibration Error Estimator", published at NeurIPS 2022.☆15Updated last year
- A Data-Centric library providing a unified interface for state-of-the-art methods for hardness characterisation of data points.☆25Updated 6 months ago
- Python/R library for feature selection in neural nets. ("Feature selection using Stochastic Gates", ICML 2020)☆108Updated 3 years ago
- Utilities to perform Uncertainty Quantification on Keras Models☆119Updated last year
- Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments☆70Updated 5 years ago
- Code and documentation for experiments in the TreeExplainer paper☆185Updated 5 years ago
- NumPy library for calibration metrics☆73Updated 6 months ago
- Multiple-Output Quantile Regression☆14Updated 3 years ago
- Code implementation of our ICLR'21 paper "Calibration of Neural Networks using Splines"☆22Updated 2 years ago
- The net:cal calibration framework is a Python 3 library for measuring and mitigating miscalibration of uncertainty estimates, e.g., by a …☆366Updated last year
- Reusable BatchBALD implementation☆79Updated last year
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆52Updated 5 years ago