Alternatives and similar repositories for DiCE

Users that are interested in DiCE are comparing it to the libraries listed below

• csinva / imodels
  Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
  ☆1,572Updated 2 months ago
• SeldonIO / alibi
  Algorithms for explaining machine learning models
  ☆2,606Updated 3 months ago
• ModelOriented / DALEX
  moDel Agnostic Language for Exploration and eXplanation
  ☆1,455Updated 2 weeks ago
• salesforce / OmniXAI
  OmniXAI: A Library for eXplainable AI
  ☆963Updated last year
• Trusted-AI / AIX360
  Interpretability and explainability of data and machine learning models
  ☆1,760Updated 11 months ago
• interpretml / interpret-community
  Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world d…
  ☆438Updated 11 months ago
• dssg / aequitas
  Bias Auditing & Fair ML Toolkit
  ☆747Updated this week
• BiomedSciAI / causallib
  A Python package for modular causal inference analysis and model evaluations
  ☆809Updated 10 months ago
• carla-recourse / CARLA
  CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
  ☆298Updated 2 years ago
• mckinsey / causalnex
  A Python library that helps data scientists to infer causation rather than observing correlation.
  ☆2,430Updated last year
• EthicalML / xai
  XAI - An eXplainability toolbox for machine learning
  ☆1,224Updated 2 months ago
• sosuneko / PDPbox
  python partial dependence plot toolbox
  ☆863Updated last year
• scikit-learn-contrib / skope-rules
  machine learning with logical rules in Python
  ☆659Updated 2 years ago
• altdeep / causalAI
  The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalAI
  ☆788Updated 2 months ago
• linkedin / FastTreeSHAP
  Fast SHAP value computation for interpreting tree-based models
  ☆553Updated 2 years ago
• christophM / rulefit
  Python implementation of the rulefit algorithm
  ☆439Updated 2 years ago
• pytorch-tabular / pytorch_tabular
  A unified framework for Deep Learning Models on tabular data
  ☆1,625Updated this week
• marcotcr / anchor
  Code for "High-Precision Model-Agnostic Explanations" paper
  ☆813Updated 3 years ago
• scikit-multiflow / scikit-multiflow
  A machine learning package for streaming data in Python. The other ancestor of River.
  ☆791Updated 2 years ago
• pbiecek / xai_resources
  Interesting resources related to XAI (Explainable Artificial Intelligence)
  ☆848Updated 3 years ago
• BCG-X-Official / facet
  Human-explainable AI.
  ☆529Updated last week
• jphall663 / interpretable_machine_learning_with_python
  Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, …
  ☆681Updated last year
• fairlearn / fairlearn
  A Python package to assess and improve fairness of machine learning models.
  ☆2,199Updated last week
• stanfordmlgroup / ngboost
  Natural Gradient Boosting for Probabilistic Prediction
  ☆1,825Updated 2 months ago
• scikit-learn-contrib / MAPIE
  A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.
  ☆1,509Updated last week
• WillianFuks / tfcausalimpact
  Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
  ☆662Updated last year
• wangyongjie-ntu / Awesome-explainable-AI
  A collection of research materials on explainable AI/ML
  ☆1,609Updated last month
• microsoft / causica
  ☆521Updated last year
• iancovert / sage
  For calculating global feature importance using Shapley values.
  ☆284Updated last week
• cerlymarco / shap-hypetune
  A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
  ☆583Updated last year