imodels
Interpretable model library
An open-source package that provides interpretable machine learning models compatible with scikit-learn.
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
1k stars
24 watching
124 forks
Language: Jupyter Notebook
last commit: 17 days ago
Linked from 2 awesome lists
aiartificial-intelligencebayesian-rule-listdata-scienceexplainable-aiexplainable-mlimodelsinterpretabilitymachine-learningmloptimal-classification-treepythonrule-learningrulefitrulesscikit-learnstatisticssupervised-learning
academic/awesome-datascienceRelated projects:
| Repository | Description | Stars |
|---|---|---|
 h2oai/mli-resources | Provides tools and techniques for interpreting machine learning models | 484 |
 giuseppec/iml | Provides methods to interpret and explain the behavior of machine learning models | 492 |
 jphall663/interpretable_machine_learning_with_python | Teaching software developers how to build transparent and explainable machine learning models using Python | 673 |
 interpretml/dice | Provides counterfactual explanations for machine learning models to facilitate interpretability and understanding. | 1,364 |
 mayer79/flashlight | A toolset for understanding and interpreting complex machine learning models | 22 |
| csinva/hierarchical-dnn-interpretations | Provides an implementation of Hierarchical explanations for Neural Network predictions | 125 |
 understandable-machine-intelligence-lab/quantus | An eXplainable AI toolkit for evaluating and interpreting neural network explanations in various deep learning frameworks. | 556 |
 jvalegre/robert | Automated machine learning protocols for cheminformatics using Python | 38 |
 scicloj/scicloj.ml.clj-djl | Provides pre-trained machine learning models for natural language processing tasks using Clojure and the clj-djl framework. | 0 |
 deel-ai/xplique | An Explainable AI toolbox that provides various methods and tools to understand and interpret the behavior of neural networks | 644 |
 pbiecek/xaiaterum2020 | An R package and workshop materials for explaining machine learning models using explainable AI techniques | 52 |
 trusted-ai/aix360 | A toolkit for explaining complex AI models and data-driven insights | 1,633 |
 sergioburdisso/pyss3 | A Python package implementing an interpretable machine learning model for text classification with visualization tools | 336 |
 modeloriented/dalex | A tool to help understand and explain the behavior of complex machine learning models | 1,375 |
 360cvgroup/360vl | A large multi-modal model developed using the Llama3 language model, designed to improve image understanding capabilities. | 30 |