build_xspliner: Helper function for building GLM object with transformed...

In xspliner: Assisted Model Building, using Surrogate Black-Box Models to Train Interpretable Spline Based Additive Models

Description

Helper function for building GLM object with transformed variables.

Usage

build_xspliner(formula, model, data, xf_opts = xf_opts_default,
  xs_opts = xs_opts_default, link = "identity", family = "gaussian",
  env = parent.frame(), compare_stat = aic, control, ...)

Arguments

formula	xspliner-specific formula object. Check vignette("xspliner") for more details.
model	Predictive model. Basic model used for extracting predictors transformation.
data	Training data of model.
xf_opts	Formula parameters used for factor variable transformations inherited from factorMerger package.
xs_opts	Predictive model response method and approximation parameters used for quantitative.
link	Link function that should be used in final model. The passed is used when cannot be extracted from model. By default 'identity'. See family for possibilities.
family	Family of response variable that should be used in final model. The passed is used when cannot be extracted from model. By default 'gaussian'. See family for possibilities.
env	Environment in which optional variables passed into parameters are stored.
compare_stat	Function of linear model (lm function output). Statistic that measures if linear model is better that transformed one. See stats.
control	Fitting settings. See glm.control.
...	Another parameters passed from chosen method. Not used.

xspliner documentation built on Sept. 26, 2019, 1:02 a.m.