Alternatives and similar repositories for tds_features_important_doesnt_mean_good

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

• solegalli / feature_engine
  Feature engineering package with sklearn like functionality
  ☆56Updated last year
• rabia174 / ConformaSight
  Conformal Prediction-Based Global and Model Agnostic Explainability for Classification tasks.
  ☆26Updated 11 months ago
• modeva-ai / Modeva
  Integrated tool for model development and validation
  ☆33Updated 2 months ago
• Moffran / calibrated_explanations
  Repository for the explanation method Calibrated Explanations (CE)
  ☆71Updated last week
• 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 3 years ago
• smazzanti / valicast
  Validation for forecasts
  ☆17Updated 2 years ago
• MartinWeigl / pycaleva
  A framework for calibration measurement of binary probabilistic models
  ☆29Updated last year
• predict-idlab / powershap
  A power-full Shapley feature selection method.
  ☆211Updated 3 months ago
• microsoft / CBM
  Cyclic Boosting Machines - an explainable supervised machine learning algorithm
  ☆62Updated last year
• superlinear-ai / conformal-tights
  👖 Conformal Tights adds conformal prediction of coherent quantiles and intervals to any scikit-learn regressor or Darts forecaster
  ☆115Updated 3 months ago
• tblume1992 / MFLES
  ☆115Updated last year
• MLDreamer / Linkedin-posts
  ☆25Updated this week
• atif-hassan / FRUFS
  An unsupervised feature selection technique using supervised algorithms such as XGBoost
  ☆91Updated 2 years ago
• ip200 / venn-abers
  Python implementation of binary and multi-class Venn-ABERS calibration
  ☆191Updated 3 months ago
• erdogant / hgboost
  hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating t…
  ☆64Updated 10 months ago
• hsbc / tslumen
  A library for Time Series EDA (exploratory data analysis)
  ☆72Updated last year
• Blue-Yonder-OSS / cyclic-boosting
  implementation of Cyclic Boosting machine learning algorithms
  ☆94Updated last year
• takechanman1228 / Effective-Uplift-Modeling
  ☆25Updated last year
• AutoViML / pandas_dq
  Find data quality issues and clean your data in a single line of code with a Scikit-Learn compatible Transformer.
  ☆135Updated 2 years ago
• lavinei / pybats
  Bayesian time series forecasting and decision analysis
  ☆120Updated 2 years ago
• cerlymarco / tspiral
  A python package for time series forecasting with scikit-learn estimators.
  ☆162Updated last year
• zillow / quantile-forest
  Quantile Regression Forests compatible with scikit-learn.
  ☆251Updated last week
• kvnkho / pydata-timeseries-forecasting
  Material for PyData NYC Tutorial on Large Scale Timeseries Forecasting
  ☆27Updated 2 years ago
• sktime / sktime-tutorial-pydata-berlin-2022
  ☆38Updated 3 years ago
• carlomazzaferro / scikit-hts-examples
  Example usage of scikit-hts
  ☆57Updated 3 years ago
• ModelOriented / SAFE
  Surrogate Assisted Feature Extraction
  ☆37Updated 4 years ago
• feature-engine / feature-engine-examples
  ☆36Updated 11 months ago
• ThomasBury / arfs
  All Relevant Feature Selection
  ☆142Updated 9 months ago
• Valdecy / pyInterDemand
  A python Library for Intermittent Demand Methods: Croston, SBA, SBJ, TSB, HES, LES and SES
  ☆39Updated last year
• carlomazzaferro / scikit-hts
  Hierarchical Time Series Forecasting with a familiar API
  ☆226Updated 2 years ago