mateoespinosa / remixLinks
Rule Extraction Methods for Interactive eXplainability
☆48Updated 3 years ago
Alternatives and similar repositories for remix
Users that are interested in remix are comparing it to the libraries listed below
Sorting:
- For calculating Shapley values via linear regression.☆71Updated 4 years ago
- This repository captures source code and data sets for our paper at the Causal Discovery & Causality-Inspired Machine Learning Workshop a…☆62Updated last year
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 4 years ago
- Code for "NODE-GAM: Neural Generalized Additive Model for Interpretable Deep Learning"☆46Updated 3 years ago
- Neural Additive Models (Google Research)☆73Updated 4 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated 11 months ago
- An open-source package of causal feature selection and causal (Bayesian network) structure learning (C/C++ version)☆64Updated 5 years ago
- Python code for NeurIPS 2018 paper "Causal Inference and Mechanism Clustering of A Mixture of Additive Noise Models"☆23Updated 6 years ago
- pyCausalFS：A Python Library of Causality-based Feature Selection for Causal Structure Learning and Classification☆71Updated 5 years ago
- Active Bayesian Causal Inference (Neurips'22)☆59Updated last year
- Example causal datasets with consistent formatting and ground truth☆100Updated 7 months ago
- Causing: CAUsal INterpretation using Graphs☆60Updated last week
- Code for ICML 2020 paper: "Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders" by I. …☆52Updated 4 years ago
- Generalized additive model with pairwise interactions☆67Updated last year
- Python package for (conditional) independence testing and statistical functions related to causality.☆29Updated this week
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆62Updated 4 months ago
- Fast and incremental explanations for online machine learning models. Works best with the river framework.☆55Updated 11 months ago
- Implementation for Stankevičiūtė et al. "Conformal time-series forecasting", NeurIPS 2021.☆77Updated last year
- A Python package for unwrapping ReLU DNNs☆68Updated last year
- ☆91Updated 4 years ago
- Multi-Objective Counterfactuals☆43Updated 3 years ago
- Model Agnostic Counterfactual Explanations☆88Updated 3 years ago
- CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms☆297Updated 2 years ago
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆25Updated 3 years ago
- (Conditional) Independence testing & Markov blanket feature selection using k-NN mutual information and conditional mutual information es…☆31Updated 5 years ago
- [ NeurIPS 2023 ] Official Codebase for "Conformal Meta-learners for Predictive Inference of Individual Treatment Effects"☆45Updated 2 years ago
- Discrete, Gaussian, and Heterogenous HMM models full implemented in Python. Missing data, Model Selection Criteria (AIC/BIC), and Semi-Su…☆80Updated 2 years ago
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆45Updated 6 months ago
- Multiple Generalized Additive Models implemented in Python (EBM, XGB, Spline, FLAM). Code for our KDD 2021 paper "How Interpretable and T…☆13Updated 4 years ago
- The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).☆221Updated 2 years ago