tidytune leverages the `rsample` and `recipes` packages to do hyperparameter tuning, tidy style.There are many benefits of using tidy data principles, one of which is the ability to reuse existing tools. Another advantage in the case of machine learning hyperparameter optimization is the opportunity to learn about the model itself, using the parameters and their performance as modeling data, passed to a surrogate (or meta) model.
Package details |
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Maintainer | |
License | GPL-3 |
Version | 0.0.1.9003 |
URL | https://github.com/artichaud1/tidytune |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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