spread.boot: bootstrap spread scores across several runs of the ctree...

Description Usage Arguments

View source: R/util-tree.R

Description

This function repeatedly randomly sub-samples the passed data.frame to provide points for classificaiton by the passed ctree model and calculates the resulting spread score for classifications of each subset and returns a vector of the resulting scores. It is useful for determining the robustness of the spread score for a particular data set.

Usage

1
spread.boot(df, df.ct, nRun = 100, nSample = NULL, responseVar, ignoreCols)

Arguments

df

data.frame with response variable to be explained and all explanatory variables to be used in ctree classificaiton

df.ct

ctree already trained on data, that is used to classify the data points in each sub sample.

nRun

number of bootstrapping runs to perform

nSample

number of samples (with replacement) for each run

responseVar

the name of the variable that the ctree is trying to explain

ignoreCols

an optional list of columns in df, but that should be excluded from the ctree modeling


ConvergenceDA/visdom documentation built on May 6, 2019, 12:51 p.m.