explainx
Model explainer
Provides a framework to understand and explain the behavior of machine learning models used in data science applications.
Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ [email protected]
417 stars
10 watching
54 forks
Language: Jupyter Notebook
last commit: 3 months ago
Linked from 2 awesome lists
aws-sagemakerbiasblackboxexplainabilityexplainable-aiexplainable-artificial-intelligenceexplainable-mlexplainxinterpretabilityinterpretable-aiinterpretable-machine-learningmachine-learningmachine-learning-interpretabilityscikit-learntransparencyxai
Related projects:
Repository | Description | Stars |
---|---|---|
modeloriented/dalex | A tool to help understand and explain the behavior of complex machine learning models | 1,375 |
modeloriented/modelstudio | A tool for creating interactive, model-agnostic explanations of machine learning models in R | 326 |
pbiecek/xaiaterum2020 | An R package and workshop materials for explaining machine learning models using explainable AI techniques | 52 |
interpretml/dice | Provides counterfactual explanations for machine learning models to facilitate interpretability and understanding. | 1,364 |
pair-code/what-if-tool | An interactive tool for exploring and understanding the behavior of machine learning models | 917 |
trusted-ai/aix360 | A toolkit for explaining complex AI models and data-driven insights | 1,633 |
modeloriented/ibreakdown | A tool for explaining predictions from machine learning models by attributing them to specific input variables and their interactions. | 81 |
rmarko/explainprediction | An R package for explaining the predictions made by machine learning models in data science applications. | 2 |
understandable-machine-intelligence-lab/quantus | An eXplainable AI toolkit for evaluating and interpreting neural network explanations in various deep learning frameworks. | 556 |
h2oai/mli-resources | Provides tools and techniques for interpreting machine learning models | 484 |
marcotcr/anchor | Provides a method to generate explanations for predictions made by any black box classifier. | 798 |
jphall663/interpretable_machine_learning_with_python | Teaching software developers how to build transparent and explainable machine learning models using Python | 673 |
ethicalml/xai | An eXplainability toolbox for machine learning that enables data analysis and model evaluation to mitigate biases and improve performance | 1,125 |
marcelrobeer/explabox | An exploratory tool for analyzing and understanding machine learning models | 15 |
deel-ai/xplique | An Explainable AI toolbox that provides various methods and tools to understand and interpret the behavior of neural networks | 644 |