baggtree {PPforest} | R Documentation |
For each bootstrap sample grow a projection pursuit tree (PPtree object).
Description
For each bootstrap sample grow a projection pursuit tree (PPtree object).
Usage
baggtree(
data,
y,
m = 500,
PPmethod = "LDA",
lambda = 0.1,
size.p = 1,
parallel = FALSE,
cores = 2
)
Arguments
data |
Data frame with the complete data set. |
y |
A character with the name of the y 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. |
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 if size.p= 1 it is bagging and if size.p<1 it is a forest. |
parallel |
logical condition, if it is TRUE then parallelize the function |
cores |
number of cores used in the parallelization |
Value
data frame with trees_pp output for all the bootstraps samples.