Alternatives and similar repositories for ITMO_FS:

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

• chasedehan / BoostARoota
  A fast xgboost feature selection algorithm
  ☆221Updated 3 years ago
• Sundar0989 / XuniVerse
  xverse (XuniVerse) is collection of transformers for feature engineering and feature selection
  ☆117Updated last year
• ThomasBury / arfs
  All Relevant Feature Selection
  ☆131Updated last month
• Alex-Lekov / AutoML_Alex
  State-of-the art Automated Machine Learning python library for Tabular Data
  ☆228Updated last year
• sberbank-ai-lab / AutoMLWhitebox
  Tool for whitebox (binning + logreg) model development
  ☆77Updated 3 years ago
• sb-ai-lab / Py-Boost
  Python based GBDT implementation on GPU. Efficient multioutput (multiclass/multilabel/multitask) training
  ☆179Updated 8 months ago
• predict-idlab / powershap
  A power-full Shapley feature selection method.
  ☆203Updated 10 months ago
• Ekeany / Boruta-Shap
  A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.
  ☆611Updated last year
• LocalCascadeEnsemble / LCE
  Random Forest or XGBoost? It is Time to Explore LCE
  ☆66Updated last year
• DenisVorotyntsev / AutoSeries
  Public solution for AutoSeries competition
  ☆72Updated 5 years ago
• sberbank-ai-lab / Py-Boost
  Python based GBDT implementation
  ☆29Updated 3 years ago
• DenisVorotyntsev / CategoricalEncodingBenchmark
  Benchmarking different approaches for categorical encoding for tabular data
  ☆173Updated 2 years ago
• manuel-calzolari / sklearn-genetic
  Genetic feature selection module for scikit-learn
  ☆324Updated last year
• danilkolikov / fsfc
  Feature Selection for Clustering
  ☆96Updated 6 years ago
• jhwjhw0123 / Imbalance-XGBoost
  XGBoost for label-imbalanced data: XGBoost with weighted and focal loss functions
  ☆318Updated last year
• ing-bank / probatus
  SHAP RFE(CV)-based validation for (multiclass) linear and tree-based models.
  ☆135Updated this week
• SylwiaOliwia2 / xgboost-AutoTune
  Wrap-up to automatically tune xgboost in Python.
  ☆80Updated 3 years ago
• kaushalshetty / FeatureSelectionGA
  Feature Selection using Genetic Algorithm (DEAP Framework)
  ☆367Updated 2 years ago
• scikit-learn-contrib / stability-selection
  scikit-learn compatible implementation of stability selection.
  ☆212Updated last year
• aimclub / FEDOT
  Automated modeling and machine learning framework FEDOT
  ☆663Updated last week
• tblume1992 / LazyProphet
  Time Series Forecasting with LightGBM
  ☆83Updated 2 years ago
• manuel-calzolari / shapicant
  Feature selection package based on SHAP and target permutation, for pandas and Spark
  ☆30Updated 3 years ago
• ITMO-NSS-team / fedot-examples
  The repository contains examples for the AutoML framework FEDOT
  ☆50Updated last year
• cod3licious / autofeat
  Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
  ☆509Updated this week
• ealcobaca / pymfe
  Python Meta-Feature Extractor package.
  ☆131Updated 9 months ago
• KaveIO / PhiK
  Phi_K correlation analyzer library
  ☆162Updated 2 months ago
• jaswinder9051998 / zoofs
  zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range fr…
  ☆245Updated 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…
  ☆62Updated 3 weeks ago
• ryancheunggit / tabular_dae
  ☆52Updated 2 years ago
• EpistasisLab / scikit-rebate
  A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
  ☆416Updated 2 years ago