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

In PPforest: Projection Pursuit Classification Forest

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.