Feature_Selection_BIC: Title Feature Selection Using BIC

In HBPMedical/CCC: A wrapper to run the 3C methodology

Description

Title Feature Selection Using BIC

Usage

Feature_Selection_BIC(x, y, nbest = 1, nvmax = 12, nmin = 4,
  plot.BIC = FALSE)

Arguments

x	Data matrix
y	response vector (must be numeric?)
nbest	number of subsets of each size to record
nvmax	maximum size of subsets to examine
nmin	number of minimum varibles to be included in the suggested final model
plot.BIC	if TRUE (default) the function plots a table of models showing which variables are in each model. The models are ordered by the specified model selection statistic.

Value

vector with the names of variables of the model with minimum BIC between the models including more then 'nmin' variables' of regsubsets object

Examples

#  Feature_Selection_BIC(x[, 1:30], y, nbest=1, nvmax=5, plot.BIC=TRUE, nmin=4)

HBPMedical/CCC documentation built on May 28, 2019, 12:40 p.m.