dials: Tools for working with tuning parameters
dials provides a framework for defining, creating, and
managing tuning parameters for modeling. It contains functions
to create tuning parameter objects (e.g. mtry() or
penalty()) and others for creating tuning grids (e.g.
grid_regular()). There are also functions for generating
random values or specifying a transformation of the parameters.
Maintainer: Hannah Frick hannah@rstudio.com
Authors:
Max Kuhn max@rstudio.com
Other contributors:
RStudio [copyright holder]
Useful links:
# Suppose we were tuning a linear regression model that was fit with glmnet # and there was a predictor that used a spline basis function to enable a # nonlinear fit. We can use `penalty()` and `mixture()` for the glmnet parts # and `deg_free()` for the spline. # A full 3^3 factorial design where the regularization parameter is on # the log scale: simple_set <- grid_regular(penalty(), mixture(), deg_free(), levels = 3) simple_set # A random grid of 5 combinations set.seed(362) random_set <- grid_random(penalty(), mixture(), deg_free(), size = 5) random_set # A small space-filling design based on experimental design methods: design_set <- grid_max_entropy(penalty(), mixture(), deg_free(), size = 5) design_set
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