Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
☆1,588May 14, 2026Updated last week
Alternatives and similar repositories for imodels
Users that are interested in imodels are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- machine learning with logical rules in Python☆659Jan 31, 2024Updated 2 years ago
- Feature engineering and selection open-source Python library compatible with sklearn.☆2,238Mar 28, 2026Updated last month
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,547Updated this week
- Fit interpretable models. Explain blackbox machine learning.☆6,852Updated this week
- Extra blocks for scikit-learn pipelines.☆1,392May 11, 2026Updated last week
- Wordpress hosting with auto-scaling - Free Trial Offer • AdFully Managed hosting for WordPress and WooCommerce businesses that need reliable, auto-scalable performance. Cloudways SafeUpdates now available.
- Python implementation of the rulefit algorithm☆446Oct 8, 2023Updated 2 years ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,511Jul 13, 2025Updated 10 months ago
- 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models☆3,217Apr 28, 2026Updated 3 weeks ago
- Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshad…☆678Feb 19, 2025Updated last year
- Algorithms for explaining machine learning models☆2,628Oct 17, 2025Updated 7 months ago
- A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.☆652Feb 19, 2024Updated 2 years ago
- moDel Agnostic Language for Exploration and eXplanation☆1,468Jan 20, 2026Updated 4 months ago
- Doubt your data, find bad labels.☆516Jul 15, 2024Updated last year
- Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.☆2,485Feb 11, 2026Updated 3 months ago
- Simple, predictable pricing with DigitalOcean hosting • AdAlways know what you'll pay with monthly caps and flat pricing. Enterprise-grade infrastructure trusted by 600k+ customers.
- Interpret text data with LLMs (sklearn compatible).☆175Apr 22, 2026Updated last month
- Natural Gradient Boosting for Probabilistic Prediction☆1,874Mar 24, 2026Updated last month
- Machine learning with dataframes☆1,612May 12, 2026Updated last week
- A library of sklearn compatible categorical variable encoders☆2,489May 5, 2026Updated 2 weeks ago
- Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML va…☆4,017Dec 28, 2025Updated 4 months ago
- A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.☆584Jun 8, 2024Updated last year
- Algorithms for outlier, adversarial and drift detection☆2,515Dec 11, 2025Updated 5 months ago
- PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics☆1,285Mar 30, 2025Updated last year
- An extension of XGBoost to probabilistic modelling☆709Dec 11, 2025Updated 5 months 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.
- 🌊 Online machine learning in Python☆5,818May 12, 2026Updated last week
- Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ra…☆767Aug 20, 2024Updated last year
- Fast SHAP value computation for interpreting tree-based models☆557Jun 26, 2023Updated 2 years ago
- Natural Intelligence is still a pretty good idea.☆832Mar 9, 2026Updated 2 months ago
- A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.☆4,349Updated this week
- Uplift modeling and causal inference with machine learning algorithms☆5,841May 16, 2026Updated last week
- A game theoretic approach to explain the output of any machine learning model.☆25,431May 16, 2026Updated last week
- Linear Prediction Model with Automated Feature Engineering and Selection Capabilities☆537Jan 6, 2026Updated 4 months ago
- DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a uni…☆8,116Updated this week
- Deploy on Railway without the complexity - Free Credits Offer • AdConnect your repo and Railway handles the rest with instant previews. Quickly provision container image services, databases, and storage volumes.
- EvalML is an AutoML library written in python.☆848Jan 14, 2026Updated 4 months ago
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.☆2,051May 7, 2026Updated 2 weeks ago
- nannyml: post-deployment data science in python☆2,139Jul 12, 2025Updated 10 months ago
- Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual expl…☆522Feb 14, 2026Updated 3 months ago
- Python Interface of the Scalable Bayesian Rule Lists☆20Feb 2, 2020Updated 6 years ago
- Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation☆3,260Updated this week
- A Python library that helps data scientists to infer causation rather than observing correlation.☆2,464Jun 26, 2024Updated last year