R/RcppExports.R

Defines functions rangerCpp

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

rangerCpp <- function(treetype, dependent_variable_name, input_data, variable_names, mtry, num_trees, verbose, seed, num_threads, write_forest, importance_mode_r, min_node_size, split_select_weights, use_split_select_weights, always_split_variable_names, use_always_split_variable_names, status_variable_name, prediction_mode, loaded_forest, sparse_data, sample_with_replacement, probability, unordered_variable_names, use_unordered_variable_names, save_memory, splitrule_r, case_weights, use_case_weights, predict_all, keep_inbag, sample_fraction, alpha, minprop, holdout, prediction_type_r, borders, userps) {
    .Call('_ordinalForest_rangerCpp', PACKAGE = 'ordinalForest', treetype, dependent_variable_name, input_data, variable_names, mtry, num_trees, verbose, seed, num_threads, write_forest, importance_mode_r, min_node_size, split_select_weights, use_split_select_weights, always_split_variable_names, use_always_split_variable_names, status_variable_name, prediction_mode, loaded_forest, sparse_data, sample_with_replacement, probability, unordered_variable_names, use_unordered_variable_names, save_memory, splitrule_r, case_weights, use_case_weights, predict_all, keep_inbag, sample_fraction, alpha, minprop, holdout, prediction_type_r, borders, userps)
}

Try the ordinalForest package in your browser

Any scripts or data that you put into this service are public.

ordinalForest documentation built on Dec. 1, 2022, 1:25 a.m.