Python implementation of binary and multi-class Venn-ABERS calibration

Fast implementation of Venn-ABERS probabilistic predictors

Multi-class probabilistic classification using inductive and cross Venn–Abers predictors

An implementation of Self-Calibrating Conformal Prediction, accepted to Neurips 2024. SC-CP combines Venn-Abers calibration and conformal prediction to deliver calibrated point predictions alongside prediction intervals with finite-sample validity conditional on these predictions.

An Implementation of Venn-ABERS predictor

Predictive target profile using Cross Venn-ABER predictors

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This repository contains research about the use of Venn Abers predictors to learn from uncertain data in a context of self learning.

Code for the paper "Calibration of Natural Language Understanding Models with Venn--ABERS Predictors" by P. Giovannotti

Code for submitted paper

Dataset repository for the paper "ASAP Hardware Failure-Cause Identification in Microwave Networks Using Venn-Abers Predictors", IEEE Transactions on Network and Service Management, 2024

Binary classifier with Venn-ABERS calibration, temporal validation, hyper-parameter optimisation, and fraud detection out of the box

A conda-smithy repository for venn-abers.

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Repository accompanying the paper Inductive Venn–Abers and related regressors

Code and data for "Safe Deployment of Selective Classifiers: Reliable Performance Estimation with Venn-Abers Predictors"