ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based models.
☆102Aug 31, 2022Updated 3 years ago
Alternatives and similar repositories for acv00
Users that are interested in acv00 are comparing it to the libraries listed below
Sorting:
- Adaptive Conformal Prediction Intervals (ACPI) is a Python package that enhances the Predictive Intervals provided by the split conformal…☆30Mar 23, 2023Updated 2 years ago
- Prediction Explanations Clustering☆10Oct 19, 2023Updated 2 years ago
- A scikit-learn-compatible module for comparing imputation methods.☆140Jan 1, 2026Updated 2 months ago
- End-to-end machine learning project for rices detection☆47Jun 1, 2022Updated 3 years ago
- Surrogate Assisted Feature Extraction☆37Aug 19, 2021Updated 4 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆78Mar 22, 2023Updated 2 years ago
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,523Updated this week
- 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models☆3,149Feb 6, 2026Updated last month
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,572Feb 24, 2026Updated last week
- Référentiel d'évaluation data science responsable et de confiance☆74Sep 12, 2024Updated last year
- A python library to build Model Trees with Linear Models at the leaves.☆389Jul 19, 2024Updated last year
- Code for the paper "SMACE: A New Method for the Interpretability of Composite Decision Systems", ECML 2022☆15Apr 17, 2023Updated 2 years ago
- Enhanced Explainable Neural Network☆10Dec 25, 2021Updated 4 years ago
- 📧 Melusine: Use python to automatize your email processing workflow☆363Feb 26, 2026Updated last week
- Learning clinical-decision rules with interpretable models.☆21Aug 10, 2023Updated 2 years ago
- Fast SHAP value computation for interpreting tree-based models☆554Jun 26, 2023Updated 2 years ago
- A toolbox for fair and explainable machine learning☆55Jun 17, 2024Updated last year
- Source Code for 'Implementing Machine Learning for Finance' by Tshepo Chris Nokeri☆34May 28, 2021Updated 4 years ago
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆25Jun 4, 2022Updated 3 years ago
- machine learning with logical rules in Python☆658Jan 31, 2024Updated 2 years ago
- Automated Transparent Genetic Feature Engineering☆22Jul 6, 2023Updated 2 years ago
- AntakIA is THE tool to explain an ML model or replace it with a collection of basic explainable models.☆14Feb 16, 2026Updated 2 weeks ago
- ☆12May 20, 2021Updated 4 years ago
- Optimal Sparse Decision Trees☆108Apr 27, 2023Updated 2 years ago
- A rule-based aproach to explain the output of any machine learning model☆15Apr 4, 2024Updated last year
- This experimental tool leverages Google's Gemini 2.5 Flash Preview model to parse complex tables from PDF documents and convert them into…☆14May 16, 2025Updated 9 months ago
- Developmental tools to detect data drift☆18Feb 27, 2024Updated 2 years ago
- A scikit-learn compatible estimator based on business-rules with interactive dashboard included☆28Aug 17, 2021Updated 4 years ago
- For calculating global feature importance using Shapley values.☆285Updated this week
- Generalized additive model with pairwise interactions☆69Mar 22, 2024Updated last year
- Simplified tree-based classifier and regressor for interpretable machine learning (scikit-learn compatible)☆46Feb 12, 2021Updated 5 years ago
- Rule Extraction Methods for Interactive eXplainability☆48Jun 6, 2022Updated 3 years ago
- For calculating Shapley values via linear regression.☆73Jun 6, 2021Updated 4 years ago
- Code repository for the paper "Towards a Comprehensive Evaluation of Dimension Reduction Methods for Data Visualization"☆14Jul 4, 2024Updated last year
- Experiments with experimental rule-based models to go along with imodels.☆18Updated this week
- A straightforward implementation of EGBM-based Generalized Additive Model☆14Oct 15, 2020Updated 5 years ago
- Multiple Generalized Additive Models implemented in Python (EBM, XGB, Spline, FLAM). Code for our KDD 2021 paper "How Interpretable and T…☆13Aug 15, 2021Updated 4 years ago
- Utilities for working with formulas, expressions, calls and other R objects☆17Nov 18, 2018Updated 7 years ago
- A logical, reasonably standardized, but flexible project structure for conducting ml research 🍪☆18Jan 23, 2026Updated last month