Alternatives and similar repositories for feature-engineering-and-feature-selection

Users that are interested in feature-engineering-and-feature-selection are comparing it to the libraries listed below

• kaushalshetty / FeatureSelectionGA
  Feature Selection using Genetic Algorithm (DEAP Framework)
  ☆370Updated 2 years ago
• ashishpatel26 / Amazing-Feature-Engineering
  Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features…
  ☆741Updated last month
• duxuhao / Feature-Selection
  Features selector based on the self selected-algorithm, loss function and validation method
  ☆681Updated 6 years ago
• solegalli / feature-selection-for-machine-learning
  Code repository for the online course Feature Selection for Machine Learning
  ☆324Updated 9 months ago
• WillKoehrsen / feature-selector
  Feature selector is a tool for dimensionality reduction of machine learning datasets
  ☆2,241Updated last year
• YC-Coder-Chen / feature-engineering-handbook
  A practical feature engineering handbook
  ☆329Updated 5 years ago
• abhishekkrthakur / autoxgb
  XGBoost + Optuna
  ☆717Updated 11 months ago
• alicezheng / feature-engineering-book
  Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018
  ☆1,463Updated 5 years ago
• yzhao062 / combo
  (AAAI' 20) A Python Toolbox for Machine Learning Model Combination
  ☆658Updated 2 years ago
• anujdutt9 / Feature-Selection-for-Machine-Learning
  Methods with examples for Feature Selection during Pre-processing in Machine Learning.
  ☆363Updated 5 years ago
• WillKoehrsen / hyperparameter-optimization
  Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms
  ☆634Updated 2 years ago
• analyticalmindsltd / smote_variants
  A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection fea…
  ☆671Updated last year
• scikit-learn-contrib / boruta_py
  Python implementations of the Boruta all-relevant feature selection method.
  ☆1,584Updated last year
• feature-engine / feature_engine
  Feature engineering package with sklearn like functionality
  ☆2,114Updated 2 weeks ago
• rasgointelligence / feature-engineering-tutorials
  Data Science Feature Engineering and Selection Tutorials
  ☆286Updated 2 months ago
• cod3licious / autofeat
  Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
  ☆522Updated 5 months ago
• cerlymarco / shap-hypetune
  A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
  ☆578Updated last year
• guillermo-navas-palencia / optbinning
  Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual expl…
  ☆489Updated 2 months ago
• Yimeng-Zhang / Rule_Extraction_from_Trees
  A toolkit for extracting comprehensible rules from tree-based algorithms
  ☆43Updated 6 years ago
• jundongl / scikit-feature
  open-source feature selection repository in python
  ☆1,547Updated last year
• aikho / awesome-feature-engineering
  A curated list of resources dedicated to Feature Engineering Techniques for Machine Learning
  ☆595Updated 6 years ago
• solegalli / machine-learning-imbalanced-data
  Code repository for the online course Machine Learning with Imbalanced Data
  ☆182Updated 8 months ago
• smazzanti / mrmr
  mRMR (minimum-Redundancy-Maximum-Relevance) for automatic feature selection at scale.
  ☆603Updated 9 months ago
• Ekeany / Boruta-Shap
  A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.
  ☆628Updated last year
• cuge1995 / awesome-time-series
  list of papers, code, and other resources
  ☆1,007Updated last week
• jrzaurin / LightGBM-with-Focal-Loss
  An implementation of the focal loss to be used with LightGBM for binary and multi-class classification problems
  ☆255Updated 5 years ago
• AutoViML / Auto_TS
  Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ra…
  ☆760Updated last year
• jhwjhw0123 / Imbalance-XGBoost
  XGBoost for label-imbalanced data: XGBoost with weighted and focal loss functions
  ☆327Updated last year
• jiwidi / time-series-forecasting-with-python
  A use-case focused tutorial for time series forecasting with python
  ☆676Updated 2 years ago
• scikit-learn-contrib / category_encoders
  A library of sklearn compatible categorical variable encoders
  ☆2,455Updated 2 months ago