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README_Feature Engineering Automation.md

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Feature Engineering Automation

  • auto-sklearn - Framework to automate algorithm and hyperparameter tuning for sklearn
  • AutoML-GS - Automatic feature and model search with code generation in Python, on top of common data science libraries (tensorflow, sklearn, etc)
  • automl - Automated feature engineering, feature/model selection, hyperparam. optimisation
  • Colombus - A scalable framework to perform exploratory feature selection implemented in R
  • Feature Engine - Feature-engine is a Python library that contains several transformers to engineer features for use in machine learning models.
  • Featuretools - An open source framework for automated feature engineering
  • sklearn-deap Use evolutionary algorithms instead of gridsearch in scikit-learn.
  • TPOT - Automation of sklearn pipeline creation (including feature selection, pre-processor, etc)
  • tsfresh - Automatic extraction of relevant features from time series
  • mljar-supervised - An Automated Machine Learning (AutoML) python package for tabular data. It can handle: Binary Classification, MultiClass Classification and Regression. It provides feature engineering, explanations and markdown reports.