Alternatives and similar repositories for shap-clustering

Users that are interested in shap-clustering are comparing it to the libraries listed below

• soda-inria / survival-analysis-benchmark
  Exploratory repository to study predictive survival analysis models
  ☆34Updated 2 years ago
• ykwon0407 / WeightedSHAP
  WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)
  ☆160Updated 2 years ago
• AidanCooper / shap-analysis-guide
  How to Interpret SHAP Analyses: A Non-Technical Guide
  ☆56Updated 3 years ago
• ModelOriented / SAFE
  Surrogate Assisted Feature Extraction
  ☆37Updated 3 years ago
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆74Updated last year
• larsroemheld / causalinf_ex_elasticity
  A full example for causal inference on real-world retail data, for elasticity estimation
  ☆50Updated 3 years ago
• lucazav / binclass-tools
  The binclass-tools package contains a set of Python wrappers and interactive plots that facilitate the analysis of binary classification …
  ☆76Updated 2 years ago
• smazzanti / tds_features_important_doesnt_mean_good
  ☆32Updated last year
• flemmerich / pysubgroup
  ☆64Updated 7 months ago
• david26694 / sktools
  Helpers for scikit learn
  ☆16Updated 2 years ago
• salimamoukou / acv00
  ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any…
  ☆102Updated 2 years ago
• exploripy / exploripy
  Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.
  ☆51Updated last year
• AlxndrMlk / blogs-code
  Code for blog posts.
  ☆19Updated last year
• erdogant / clusteval
  Clusteval provides methods for unsupervised cluster validation
  ☆60Updated 2 months ago
• valeman / smote_is_what_you_dont_need
  The best repository showing why SMOTE and resampling methods might not be the answer for imbalanced data problems
  ☆46Updated 3 months ago
• pbiecek / xai_stories
  XAI Stories. Case studies for eXplainable Artificial Intelligence
  ☆29Updated 4 years ago
• Brett-Kennedy / CountsOutlierDetector
  Interpretable, intuitive outlier detector intended for categorical and numeric data.
  ☆10Updated last year
• atif-hassan / FRUFS
  An unsupervised feature selection technique using supervised algorithms such as XGBoost
  ☆90Updated last year
• RianneSchouten / pyampute
  Missing data amputation and exploration functions for Python
  ☆71Updated 2 years ago
• solegalli / feature_engine
  Feature engineering package with sklearn like functionality
  ☆54Updated 9 months ago
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆67Updated last month
• valeman / Multi-class-probabilistic-classification
  Multi-class probabilistic classification using inductive and cross Venn–Abers predictors
  ☆48Updated 3 years ago
• oegedijk / rule_estimator
  A scikit-learn compatible estimator based on business-rules with interactive dashboard included
  ☆28Updated 3 years ago
• casper-hansen / Nested-Cross-Validation
  Nested cross-validation for unbiased predictions. Can be used with Scikit-Learn, XGBoost, Keras and LightGBM, or any other estimator that…
  ☆64Updated 5 years ago
• ralphhaygood / sklearn-gbmi
  scikit-learn gradient-boosting-model interactions
  ☆25Updated 2 years ago
• adriennekline / psmpy
  propensity score matching in python
  ☆58Updated 3 weeks ago
• parrt / stratx
  stratx is a library for A Stratification Approach to Partial Dependence for Codependent Variables
  ☆66Updated last year
• pyartemis / artemis
  A Python package with explanation methods for extraction of feature interactions from predictive models
  ☆30Updated last year
• petersontylerd / mlmachine
  mlmachine accelerates machine learning experimentation
  ☆30Updated 3 years ago
• interpretml / FasterRisk
  Create sparse and accurate risk scoring systems!
  ☆37Updated 10 months ago