Alternatives and similar repositories for ClassificationThresholdTuner:

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

• AidanCooper / shap-analysis-guide
  How to Interpret SHAP Analyses: A Non-Technical Guide
  ☆52Updated 3 years ago
• donlapark / coverforest
  A simple and fast sklearn-compatible conformal predictions with random forests for both classification and regression tasks.
  ☆42Updated this week
• takechanman1228 / Effective-Uplift-Modeling
  ☆21Updated 9 months ago
• valeman / Multi-class-probabilistic-classification
  Multi-class probabilistic classification using inductive and cross Venn–Abers predictors
  ☆44Updated 2 years ago
• Brett-Kennedy / ikNN
  An interpretable kNN based on aggregating the predictions of multiple 2d spaces.
  ☆13Updated 6 months ago
• marcopeix / TimeSeriesForecastingUsingFoundationModels
  Official repository for the book Time Series Forecasting with Foundation Models
  ☆18Updated 2 weeks ago
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆64Updated last week
• smasis001 / odsc-west-2022
  Workshop for Open Data Science Conference East 2022
  ☆10Updated 2 years ago
• Brett-Kennedy / CountsOutlierDetector
  Interpretable, intuitive outlier detector intended for categorical and numeric data.
  ☆10Updated 10 months ago
• probabl-ai / youtube-appendix
  Resources for some of our education content
  ☆41Updated 2 months ago
• team-daniel / MC-CP
  All the material needed to use MC-CP and the Adaptive MC Dropout method
  ☆22Updated 7 months ago
• solegalli / feature_engine
  Feature engineering package with sklearn like functionality
  ☆54Updated 7 months ago
• ptocca / VennABERS
  Fast implementation of Venn-ABERS probabilistic predictors
  ☆72Updated last year
• zedshape / zgrouping
  ☆23Updated 3 years ago
• erdogant / hgboost
  hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating t…
  ☆64Updated last month
• rabia174 / ConformaSight
  Conformal Prediction-Based Global and Model Agnostic Explainability for Classification tasks.
  ☆25Updated 2 months ago
• jefferythewind / warpgbm
  WarpGBM: High-Speed Gradient Boosting
  ☆60Updated this week
• pycaret / examples
  Example Notebooks contributed by pycaret community!
  ☆42Updated 2 years ago
• conorosully / SHAP-tutorial
  SHAP with Python
  ☆42Updated 7 months ago
• dataman-git / Handbook-of-anomaly-detection
  ☆16Updated 6 months ago
• khuyentran1401 / prefect-docker
  Demo on how to use Prefect with Docker
  ☆25Updated 2 years ago
• vcerqueira / blog
  ☆17Updated last year
• FlorinAndrei / misc
  a catch-all repo
  ☆11Updated last year
• fonnesbeck / probabilistic_python
  PyData London 2022 Tutorial
  ☆66Updated 2 years ago
• AidanCooper / shap-clustering
  How to use SHAP values for better cluster analysis
  ☆57Updated 2 years ago
• Carl-McBride-Ellis / TOBoML
  The Orange Book of Machine Learning
  ☆39Updated last month
• dorukcanga / AutoFeatSelect
  A python library to automate feature selection process for machine learning projects.
  ☆56Updated last year
• KishManani / PyDataLondon2022
  Slides for "Feature engineering for time series forecasting" talk
  ☆59Updated 2 years ago
• tblume1992 / ConformalImpact
  Causal Impact but with MFLES and conformal prediction intervals
  ☆33Updated 3 months ago
• soda-inria / survival-analysis-benchmark
  Exploratory repository to study predictive survival analysis models
  ☆34Updated last year