make_numeric_sets: Transforming the set of predictors into a numeric set

In CARRoT: Predicting Categorical and Continuous Outcomes Using One in Ten Rule

Transforming the set of predictors into a numeric set

Description

Function which turns a set of predictors containing non-numeric variables into a fully numeric set

Usage

make_numeric_sets(a,ai,k,vari,ra,l,mode)

Arguments

a	An M x N matrix, containing all possible subsets (N overall) of the size M of predictors' indices; therefore each column of a defines a unique subset of the predictors
ai	array of indices of the array a
k	index of the array ai
vari	set of all predictors
ra	array of sample indices of vari
l	size of the sample
mode	'binary' (logistic regression), 'multin' (multinomial regression)

Details

Function transforms the whole set of predictors into a numeric set by consecutively calling function make_numeric for each predictor

Value

Returns a list containing two objects: tr and test

tr	training set transformed into a numeric one
test	test set transformed into a numeric one

See Also

make_numeric

Examples

#creating a categorical numeric variable

a<-t(rmultinom(100,1,c(0.2,0.3,0.5)))%*%c(1,2,3)

#creating an analogous non-numeric variable

c<-array(NA,100)
c[a==1]='red'
c[a==2]='green'
c[a==3]='blue'

#creating a data-set

b<-data.frame(matrix(c(a,rbinom(100,1,0.3),runif(100,0,1)),ncol=3))

#making the first column of the data-set non-numeric

b[,1]=data.frame(c)

#running the function

make_numeric_sets(combn(3,2),1:3,1,b,sample(1:100,60),100,"binary")

CARRoT documentation built on Oct. 14, 2023, 1:06 a.m.