trees_pred: Obtain predicted class for new data from baggtree function or...

View source: R/trees_pred.R

trees_predR Documentation

Obtain predicted class for new data from baggtree function or PPforest

Description

Obtain predicted class for new data from baggtree function or PPforest

Usage

trees_pred(object, xnew, parallel = FALSE, cores = 2, rule = 1)

Arguments

object

Projection pursuit classification forest structure from PPforest or baggtree

xnew

data frame with explicative variables used to get new predicted values.

parallel

logical condition, if it is TRUE then parallelize the function

cores

number of cores used in the parallelization

rule

split rule 1: mean of two group means 2: weighted mean of two group means - weight with group size 3: weighted mean of two group means - weight with group sd 4: weighted mean of two group means - weight with group se 5: mean of two group medians 6: weighted mean of two group medians - weight with group size 7: weighted mean of two group median - weight with group IQR 8: weighted mean of two group median - weight with group IQR and size

Value

predicted values from PPforest or baggtree

Examples

## Not run: 
crab.trees <- baggtree(data = crab, class = 'Type', 
m =  200, PPmethod = 'LDA', lambda = .1, size.p = 0.4 )
 
pr <- trees_pred(  crab.trees,xnew = crab[, -1], parallel= FALSE, cores = 2)

pprf.crab <- PPforest(data = crab, class = 'Type',
 std = FALSE, size.tr = 2/3, m = 100, size.p = .4, PPmethod = 'LDA', parallel = TRUE )
 
trees_pred(pprf.crab, xnew = pprf.crab$test ,parallel = TRUE)

## End(Not run)

PPforest documentation built on Sept. 10, 2022, 1:05 a.m.