Alternatives and similar repositories for detectshift:

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

• tunguz / TabularBenchmarks
  ☆200Updated 3 weeks ago
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆72Updated last year
• ip200 / venn-abers
  Python implementation of binary and multi-class Venn-ABERS calibration
  ☆155Updated 7 months ago
• ykwon0407 / WeightedSHAP
  WeightedSHAP: analyzing and improving Shapley based feature attributions (NeurIPS 2022)
  ☆160Updated 2 years ago
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆65Updated this week
• IFCA-Advanced-Computing / frouros
  Frouros: an open-source Python library for drift detection in machine learning systems.
  ☆215Updated 2 months ago
• LocalCascadeEnsemble / LCE
  Random Forest or XGBoost? It is Time to Explore LCE
  ☆66Updated last year
• gusbruschi13 / Conformal-Prediction
  Repositório contendo materiais de estudo sobre Predição Conforme.
  ☆28Updated last year
• predict-idlab / powershap
  A power-full Shapley feature selection method.
  ☆205Updated 11 months ago
• scikit-learn-contrib / hiclass
  A python library for hierarchical classification compatible with scikit-learn
  ☆131Updated last month
• rxavier / poniard
  Streamline scikit-learn model comparison.
  ☆145Updated 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…
  ☆100Updated 2 years ago
• zelros / cinnamon
  CinnaMon is a Python library which offers a number of tools to detect, explain, and correct data drift in a machine learning system
  ☆76Updated 2 years ago
• atif-hassan / FRUFS
  An unsupervised feature selection technique using supervised algorithms such as XGBoost
  ☆90Updated last year
• ysraell / random-forest-mc
  Random Forest with Dynamic Tree Selection Monte Carlo Based (RF-TSMC).
  ☆48Updated 3 weeks ago
• loft-br / xgboost-survival-embeddings
  Improving XGBoost survival analysis with embeddings and debiased estimators
  ☆333Updated 6 months ago
• soda-inria / hazardous
  Competing Risks and Survival Analysis
  ☆95Updated last week
• feedzai / fairgbm
  Train Gradient Boosting models that are both high-performance *and* Fair!
  ☆104Updated 10 months ago
• joneswack / conformal-predictions-from-scratch
  Various Conformal Prediction methods implemented from scratch in pure NumPy for an educational purpose.
  ☆212Updated last year
• KaveIO / PhiK
  Phi_K correlation analyzer library
  ☆164Updated 3 months ago
• zillow / quantile-forest
  Quantile Regression Forests compatible with scikit-learn.
  ☆227Updated last week
• 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
  ☆42Updated last month
• microsoft / CBM
  Cyclic Boosting Machines - an explainable supervised machine learning algorithm
  ☆60Updated 7 months ago
• lavinei / pybats
  Bayesian time series forecasting and decision analysis
  ☆115Updated last year
• ThomasBury / arfs
  All Relevant Feature Selection
  ☆133Updated 3 weeks ago
• MAIF / eurybia
  ⚓ Eurybia monitors model drift over time and securizes model deployment with data validation
  ☆207Updated 6 months ago
• ing-bank / probatus
  SHAP-based validation for linear and tree-based models. Applied to binary, multiclass and regression problems.
  ☆139Updated last week
• OliverHennhoefer / unquad
  Conformal Anomaly Detection
  ☆46Updated last month
• interpretml / gam-changer
  Editing machine learning models to reflect human knowledge and values
  ☆124Updated last year
• ealcobaca / pymfe
  Python Meta-Feature Extractor package.
  ☆133Updated 10 months ago