Alternatives and similar repositories for powershap:

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

• ThomasBury / arfs
  All Relevant Feature Selection
  ☆123Updated 3 months ago
• Ekeany / Boruta-Shap
  A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.
  ☆601Updated 10 months ago
• predict-idlab / tsflex
  Flexible time series feature extraction & processing
  ☆408Updated 4 months ago
• StatMixedML / LightGBMLSS
  An extension of LightGBM to probabilistic modelling
  ☆289Updated 7 months ago
• ing-bank / probatus
  Validation (like Recursive Feature Elimination for SHAP) of (multiclass) classifiers & regressors and data used to develop them.
  ☆133Updated 4 months ago
• AnotherSamWilson / miceforest
  Multiple Imputation with LightGBM in Python
  ☆369Updated 5 months ago
• tblume1992 / ThymeBoost
  Forecasting with Gradient Boosted Time Series Decomposition
  ☆191Updated last year
• zillow / quantile-forest
  Quantile Regression Forests compatible with scikit-learn.
  ☆222Updated last month
• cerlymarco / shap-hypetune
  A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
  ☆569Updated 7 months ago
• erdogant / hgboost
  hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating t…
  ☆61Updated 3 months ago
• Nixtla / tsfeatures
  Calculates various features from time series data. Python implementation of the R package tsfeatures.
  ☆378Updated 8 months 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…
  ☆100Updated 2 years ago
• cerlymarco / tspiral
  A python package for time series forecasting with scikit-learn estimators.
  ☆160Updated 9 months ago
• carlomazzaferro / scikit-hts
  Hierarchical Time Series Forecasting with a familiar API
  ☆223Updated last year
• StatMixedML / XGBoostLSS
  An extension of XGBoost to probabilistic modelling
  ☆573Updated 6 months ago
• LocalCascadeEnsemble / LCE
  Random Forest or XGBoost? It is Time to Explore LCE
  ☆67Updated last year
• CDonnerer / xgboost-distribution
  Probabilistic prediction with XGBoost.
  ☆101Updated 6 months ago
• ip200 / venn-abers
  Python implementation of binary and multi-class Venn-ABERS calibration
  ☆136Updated 4 months ago
• kearnz / autoimpute
  Python package for Imputation Methods
  ☆244Updated last year
• manuel-calzolari / shapicant
  Feature selection package based on SHAP and target permutation, for pandas and Spark
  ☆30Updated 2 years ago
• cod3licious / autofeat
  Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
  ☆507Updated 3 months ago
• cerlymarco / linear-tree
  A python library to build Model Trees with Linear Models at the leaves.
  ☆368Updated 5 months ago
• atif-hassan / FRUFS
  An unsupervised feature selection technique using supervised algorithms such as XGBoost
  ☆89Updated last year
• AutoViML / featurewiz
  Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshad…
  ☆596Updated 8 months ago
• feedzai / timeshap
  TimeSHAP explains Recurrent Neural Network predictions.
  ☆163Updated last year
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆72Updated 11 months ago
• MIDASverse / MIDASpy
  Python package for missing-data imputation with deep learning
  ☆140Updated 4 months ago
• lavinei / pybats
  Bayesian time series forecasting and decision analysis
  ☆116Updated last year
• iancovert / sage
  For calculating global feature importance using Shapley values.
  ☆259Updated this week
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆59Updated this week