data frame with trees_pp output for all the bootstraps samples.
Arguments
data
Data frame with the complete data set.
class
A character with the name of the class variable.
m
is the number of bootstrap replicates, this corresponds with the number of trees to grow. To ensure that each observation is predicted a few times we have to select this number no too small. m = 500 is by default.
PPmethod
is the projection pursuit index to be optimized, options LDA or PDA, by default it is LDA.
lambda
a parameter for PDA index
size.p
proportion of random sample variables in each split.
parallel
logical condition, if it is TRUE then parallelize the function