adaa-polsl / RuleXAI
A rule-based aproach to explain the output of any machine learning model
☆13Updated 9 months ago
Alternatives and similar repositories for RuleXAI:
Users that are interested in RuleXAI are comparing it to the libraries listed below
- Multi-Objective Counterfactuals☆41Updated 2 years ago
- This repository is used as a support for the paper "" (to be named)☆24Updated 3 years ago
- Python package for (conditional) independence testing and statistical functions related to causality.☆25Updated 2 weeks ago
- A unified interface for the estimation of causal networks☆22Updated 4 years ago
- R Implementation of FLAME, DAME, and other algorithms in the AME framework☆12Updated last year
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆24Updated 2 years ago
- A Python package with explanation methods for extraction of feature interactions from predictive models☆29Updated last year
- Conditional calibration of conformal p-values for outlier detection.☆34Updated 2 years ago
- ☆15Updated 6 years ago
- repository for R library "sbrlmod"☆25Updated 8 months ago
- Create sparse and accurate risk scoring systems!☆32Updated 5 months ago
- Variable importance via oscillations☆14Updated 4 years ago
- Local Universal Rule-based Explanations☆13Updated this week
- Code for a variety of nonlinear conditional independence tests and 'nonlinear Invariant Causal Prediction' to estimate the causal parents…☆17Updated 5 years ago
- This is a read-only mirror of the CRAN R package repository. pcalg — Methods for Graphical Models and Causal Inference. Homepage: https…☆35Updated 4 months ago
- Numerical experiments for nested cross-validation paper☆11Updated 2 years ago
- Python Interface of the Scalable Bayesian Rule Lists☆19Updated 4 years ago
- An R package for clustering mixed-type data☆16Updated last year
- An Interface to Specify Causal Graphs and Compute Balke Bounds☆15Updated last month
- An R package to assess feature importance☆33Updated 3 years ago
- Tools for causal discovery in R☆18Updated 7 months ago
- Model Agnostic Counterfactual Explanations☆87Updated 2 years ago
- Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decomposition☆16Updated 5 years ago
- Multi-Calibration & Multi-Accuracy Boosting for R☆31Updated 3 months ago
- Compute SHAP values for your tree-based models using the TreeSHAP algorithm☆82Updated 5 months ago
- Triplot: Instance- and data-level explanations for the groups of correlated features.☆9Updated 3 years ago
- Beta calibration☆27Updated 11 months ago
- An R package for causal discovery in heavy-tailed models☆12Updated 8 months ago
- Meta-Feature Extractor☆28Updated 2 years ago
- Surrogate Assisted Feature Extraction☆36Updated 3 years ago