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.
☆103Aug 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. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Adaptive Conformal Prediction Intervals (ACPI) is a Python package that enhances the Predictive Intervals provided by the split conformal…☆30Mar 23, 2023Updated 3 years ago
- A scikit-learn-compatible module for comparing imputation methods.☆140Jan 1, 2026Updated 7 months ago
- End-to-end machine learning project for rices detection☆47Jun 1, 2022Updated 4 years ago
- 📧 Melusine: Use python to automatize your email processing workflow☆363Jun 24, 2026Updated last month
- Helping humans ride the GenAI evaluation wave☆85Updated this week
- Managed hosting for WordPress and PHP on Cloudways • AdManaged hosting for WordPress, Magento, Laravel, or PHP apps, on multiple cloud providers. Deploy in minutes on Cloudways by DigitalOcean.
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,578Updated this week
- ⚓ Eurybia monitors model drift over time and securizes model deployment with data validation☆224Mar 23, 2026Updated 4 months ago
- Référentiel d'évaluation data science responsable et de confiance☆74Sep 12, 2024Updated last year
- Web app using Pyodide to demo different types of Scikit-learn classifiers☆12Apr 16, 2022Updated 4 years ago
- 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models☆3,253Jul 28, 2026Updated last week
- A toolbox for fair and explainable machine learning☆57Jun 17, 2024Updated 2 years ago
- Explain XGBoost models with the Hoeffding functional decomposition.☆16Jul 8, 2026Updated last month
- Surrogate Assisted Feature Extraction☆37Aug 19, 2021Updated 4 years ago
- Implementation of tree-structured neural networks in PyTorch.☆15Nov 15, 2021Updated 4 years ago
- AI Agents on DigitalOcean Gradient AI Platform • AdBuild production-ready AI agents using customizable tools or access multiple LLMs through a single endpoint. Create custom knowledge bases or connect external data.
- AntakIA is THE tool to explain an ML model or replace it with a collection of basic explainable models.☆14Jun 15, 2026Updated last month
- For calculating Shapley values via linear regression.☆74Jun 6, 2021Updated 5 years ago
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,612Aug 3, 2026Updated last week
- machine learning with logical rules in Python☆664Jan 31, 2024Updated 2 years ago
- Training and evaluating NBM and SPAM for interpretable machine learning.☆77Mar 22, 2023Updated 3 years ago
- A game theoretic approach to explain the output of any machine learning model.☆27Jul 16, 2023Updated 3 years ago
- A python library to build Model Trees with Linear Models at the leaves.☆389Jul 19, 2024Updated 2 years ago
- Learning clinical-decision rules with interpretable models.☆21Aug 10, 2023Updated 2 years ago
- ☆12May 20, 2021Updated 5 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- Fast SHAP value computation for interpreting tree-based models☆564Jun 26, 2023Updated 3 years ago
- For calculating global feature importance using Shapley values.☆294Updated this week
- Testing library for pyspark, inspired from pandas testing module but for pyspark, to help users write unit tests.☆21Dec 18, 2023Updated 2 years ago
- This repository contains the source code of the paper "Learning Accurate and Interpretable Decision Rule Sets from Neural Networks".☆16Jan 10, 2022Updated 4 years ago
- CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox☆47Jul 17, 2026Updated 3 weeks ago
- Ensemble wavelet based neural network for generating epidemiological forecasting (epicasting)☆15Sep 20, 2025Updated 10 months ago
- SINDy-SA framework: enhancing nonlinear system identification with sensitivity analysis☆12Apr 24, 2025Updated last year
- Code for paper "Search Methods for Sufficient, Socially-Aligned Feature Importance Explanations with In-Distribution Counterfactuals"☆18Oct 17, 2022Updated 3 years ago
- Python Interface of the Scalable Bayesian Rule Lists☆20Feb 2, 2020Updated 6 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Simplified tree-based classifier and regressor for interpretable machine learning (scikit-learn compatible)☆46Feb 12, 2021Updated 5 years ago
- Modified chesterish Jupyter theme with larger font and Iosevka webfont☆10Nov 25, 2017Updated 8 years ago
- A lightweight implementation of removal-based explanations for ML models.☆59Jul 19, 2021Updated 5 years ago
- All about explainable AI, algorithmic fairness and more☆111Sep 24, 2023Updated 2 years ago
- Automated Transparent Genetic Feature Engineering☆22Jul 6, 2023Updated 3 years ago
- IEEE TVCG Visual Analytics in Deep Learning Survey☆18Feb 11, 2021Updated 5 years ago
- BlindBox is a tool to isolate and deploy applications inside Trusted Execution Environments for privacy-by-design apps☆64Nov 13, 2023Updated 2 years ago