tidymodels/tune

Tools for tidy parameter tuning

What it solves

It simplifies the process of hyperparameter tuning for machine learning models within the tidymodels ecosystem in R.

How it works

It integrates with other tidymodels packages like recipes, parsnip, and dials to automate the search for the best model parameters to improve performance.

Who it’s for

Data scientists and machine learning practitioners using the R programming language and the tidymodels framework.

Highlights

  • Supports basic grid search for models such as SVM.
  • Enables iterative Bayesian optimization for classification models.
  • Provides tools for parallel processing and optimization.
  • Includes acquisition functions for scoring parameter combinations.

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