dials-package | R Documentation |
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@posit.co
Authors:
Max Kuhn max@posit.co
Other contributors:
Posit Software, PBC [copyright holder, funder]
Useful links:
Report bugs at https://github.com/tidymodels/dials/issues
# 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_space_filling(penalty(), mixture(), deg_free(), size = 5)
design_set
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