varImpStruct-class {MLInterfaces}R Documentation

Class "varImpStruct" - collect data on variable importance from various machine learning methods

Description

collects data on variable importance

Objects from the Class

Objects can be created by calls of the form new("varImpStruct", ...). These are matrices of importance measures with separate slots identifying algorithm generating the measures and variable names.

Slots

.Data:
Object of class "matrix" actual importance measures
method:
Object of class "character" tag
varnames:
Object of class "character" conformant vector of names of variables

Extends

Class "matrix", from data part. Class "structure", by class "matrix". Class "array", by class "matrix". Class "vector", by class "matrix", with explicit coerce. Class "vector", by class "matrix", with explicit coerce.

Methods

plot
signature(x = "varImpStruct"): make a bar plot, you can supply an argument resolveenv which will look up variable names in a translation environment
show
signature(object = "varImpStruct"): simple abbreviated display
getVarImp
signature(object = "classifOutput"): extractor of variable importance structure

Examples

library(golubEsets)
data(golubMerge)
library(hu6800)
smallG <- golubMerge[1:60,]
rf <- randomForestB( smallG, "ALL.AML", 1:40, importance=TRUE )
plot( getVarImp( rf ), n=10, resolveenv=hu6800SYMBOL )
gb <- gbmB( smallG, "ALL.AML", 1:40 , n.minobsinnode=3 , n.trees=6000)
plot( getVarImp( gb ), n=10, resolveenv=hu6800SYMBOL )

[Package MLInterfaces version 1.0.10 Index]