interpretml / TalkToEBMLinks
A Natural Language Interface to Explainable Boosting Machines
☆69Updated last year
Alternatives and similar repositories for TalkToEBM
Users that are interested in TalkToEBM are comparing it to the libraries listed below
Sorting:
- WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)☆159Updated 3 years ago
- Editing machine learning models to reflect human knowledge and values☆128Updated 2 years ago
- For calculating global feature importance using Shapley values.☆282Updated last week
- OpenXAI : Towards a Transparent Evaluation of Model Explanations☆252Updated last year
- A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.☆242Updated 5 months ago
- CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms☆298Updated 2 years ago
- Interpret text data with LLMs (sklearn compatible).☆173Updated 2 months ago
- Testing Language Models for Memorization of Tabular Datasets.☆36Updated 10 months ago
- Extending Conformal Prediction to LLMs☆68Updated last year
- TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!☆126Updated 2 years ago
- Code repository for our paper "Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift": https://arxiv.org/abs/1810.119…☆107Updated last year
- A novel approach for synthesizing tabular data using pretrained large language models☆335Updated last month
- XAI-Bench is a library for benchmarking feature attribution explainability techniques☆70Updated 2 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Updated 4 years ago
- Train Gradient Boosting models that are both high-performance *and* Fair!☆106Updated last week
- [Experimental] Causal graphs that are networkx-compliant for the py-why ecosystem.☆62Updated 2 weeks ago
- A repo for transfer learning with deep tabular models☆105Updated 2 years ago
- ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…☆102Updated 3 years ago
- A framework for prototyping and benchmarking imputation methods☆194Updated 2 years ago
- Tabular In-Context Learning☆102Updated 9 months ago
- Neural Additive Models (Google Research)☆74Updated 4 years ago
- Mixture of Decision Trees for Interpretable Machine Learning☆11Updated 4 years ago
- Experimental library integrating LLM capabilities to support causal analyses☆273Updated 2 months ago
- Python package to compute interaction indices that extend the Shapley Value. AISTATS 2023.☆18Updated 2 years ago
- GRAPL: A computational library for nonparametric structural causal modelling, analysis and inference☆83Updated last year
- Resources for Machine Learning Explainability☆86Updated last year
- scikit-activeml: A Comprehensive and User-friendly Active Learning Library☆181Updated this week
- Model Agnostic Counterfactual Explanations☆88Updated 3 years ago
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆46Updated 7 months ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Updated 2 years ago