Alternatives and similar repositories for vecstack

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

• h2oai / pystacknet
  ☆296Updated 3 years ago
• flennerhag / mlens
  ML-Ensemble – high performance ensemble learning
  ☆860Updated 2 years ago
• abhayspawar / featexp
  Feature exploration for supervised learning
  ☆761Updated 4 years ago
• rushter / heamy
  A set of useful tools for competitive data science.
  ☆553Updated 2 years ago
• sosuneko / PDPbox
  python partial dependence plot toolbox
  ☆861Updated last year
• MaxHalford / xam
  Personal data science and machine learning toolbox
  ☆366Updated 5 years ago
• RGF-team / rgf
  Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one…
  ☆382Updated 3 years ago
• limexp / xgbfir
  XGBoost Feature Interactions Reshaped
  ☆432Updated 8 years ago
• scikit-learn-contrib / boruta_py
  Python implementations of the Boruta all-relevant feature selection method.
  ☆1,599Updated 2 weeks ago
• HunterMcGushion / hyperparameter_hunter
  Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries
  ☆707Updated 4 years ago
• scikit-learn-contrib / DESlib
  A Python library for dynamic classifier and ensemble selection
  ☆495Updated last year
• Far0n / kaggletils
  ☆384Updated 8 years ago
• parrt / random-forest-importances
  Code to compute permutation and drop-column importances in Python scikit-learn models
  ☆619Updated 8 months ago
• scikit-learn-contrib / skope-rules
  machine learning with logical rules in Python
  ☆651Updated last year
• andosa / treeinterpreter
  ☆759Updated 2 years ago
• kaz-Anova / StackNet
  StackNet is a computational, scalable and analytical Meta modelling framework
  ☆1,331Updated 7 years ago
• chasedehan / BoostARoota
  A fast xgboost feature selection algorithm
  ☆228Updated 4 years ago
• EpistasisLab / scikit-rebate
  A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
  ☆420Updated 2 years ago
• WillKoehrsen / hyperparameter-optimization
  Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms
  ☆638Updated 2 years ago
• entron / entity-embedding-rossmann
  ☆871Updated 5 years ago
• aerdem4 / lofo-importance
  Leave One Feature Out Importance
  ☆853Updated 9 months ago
• christophM / rulefit
  Python implementation of the rulefit algorithm
  ☆425Updated 2 years ago
• scikit-learn-contrib / scikit-learn-contrib
  scikit-learn compatible projects
  ☆410Updated 7 months ago
• hyperopt / hyperopt-sklearn
  Hyper-parameter optimization for sklearn
  ☆1,649Updated 7 months ago
• MaxHalford / kaggle-recruit-restaurant
  Kaggle 8th place solution
  ☆107Updated 2 years ago
• scikit-multilearn / scikit-multilearn
  A scikit-learn based module for multi-label et. al. classification
  ☆953Updated last year
• Far0n / xgbfi
  XGBoost Feature Interactions & Importance
  ☆501Updated 8 years ago
• jhwjhw0123 / Imbalance-XGBoost
  XGBoost for label-imbalanced data: XGBoost with weighted and focal loss functions
  ☆331Updated last year
• viisar / brew
  ⛔️ DEPRECATED brew: Python Ensemble Learning API
  ☆303Updated 7 years ago
• titu1994 / tf-TabNet
  A Tensorflow 2.0 implementation of TabNet.
  ☆245Updated 2 years ago