dials-package: dials: Tools for working with tuning parameters

In tidymodels/dials: Tools for Creating Tuning Parameter Values

dials: Tools for working with tuning parameters

Description

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.

Author(s)

Maintainer: Hannah Frick [e-mail]

Authors:

• Max Kuhn [e-mail]

Other contributors:

• Posit Software, PBC [copyright holder, funder]

See Also

Useful links:

• https://dials.tidymodels.org

• https://github.com/tidymodels/dials

• Report bugs at https://github.com/tidymodels/dials/issues

Examples

# 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

tidymodels/dials documentation built on March 18, 2024, 6:30 a.m.