Obtain predicted class for new data from baggtree function or PPforest

Usage

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

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 used in classification (integer from 1 to 8). 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

predicted values from PPforest or baggtree