interpretml / interpretLinks
Fit interpretable models. Explain blackbox machine learning.
☆6,763Updated last week
Alternatives and similar repositories for interpret
Users that are interested in interpret are comparing it to the libraries listed below
Sorting:
- Algorithms for explaining machine learning models☆2,606Updated 3 months ago
- A curated list of awesome responsible machine learning resources.☆3,959Updated last week
- 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models☆3,112Updated last month
- A Python package to assess and improve fairness of machine learning models.☆2,189Updated 2 weeks ago
- A library for debugging/inspecting machine learning classifiers and explaining their predictions☆2,772Updated last week
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,486Updated 6 months ago
- Interpretability and explainability of data and machine learning models☆1,753Updated 10 months ago
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.☆2,467Updated 5 months ago
- XAI - An eXplainability toolbox for machine learning☆1,214Updated last month
- A python library for decision tree visualization and model interpretation.☆3,119Updated 2 weeks ago
- Hummingbird compiles trained ML models into tensor computation for faster inference.☆3,521Updated 6 months ago
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,566Updated 2 months ago
- Algorithms for outlier, adversarial and drift detection☆2,478Updated last month
- Visual analysis and diagnostic tools to facilitate machine learning model selection.☆4,392Updated 11 months ago
- A Python library that helps data scientists to infer causation rather than observing correlation.☆2,420Updated last year
- An open source python library for automated feature engineering☆7,595Updated 3 weeks ago
- Feature engineering and selection open-source Python library compatible with sklearn.☆2,178Updated last week
- A game theoretic approach to explain the output of any machine learning model.☆24,909Updated last week
- Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation☆3,234Updated 6 months ago
- A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.☆4,275Updated last week
- Natural Gradient Boosting for Probabilistic Prediction☆1,819Updated last month
- An open-source, low-code machine learning library in Python☆9,670Updated 8 months ago
- Debugging, monitoring and visualization for Python Machine Learning and Data Science☆3,464Updated 3 months ago
- moDel Agnostic Language for Exploration and eXplanation☆1,454Updated 3 months ago
- A library of sklearn compatible categorical variable encoders☆2,477Updated last week
- STUMPY is a powerful and scalable Python library for modern time series analysis☆4,051Updated 2 weeks ago
- Lime: Explaining the predictions of any machine learning classifier☆12,088Updated last year
- HiPlot makes understanding high dimensional data easy☆2,801Updated 2 years ago
- A system for quickly generating training data with weak supervision☆5,936Updated last year
- Source code/webpage/demos for the What-If Tool☆989Updated last month