Skip to content

Added R method for single tree prediction #106

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Oct 31, 2024
Merged

Added R method for single tree prediction #106

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
17 changes: 16 additions & 1 deletion R/forest.R
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -101,7 +101,7 @@ ForestSamples <- R6::R6Class(
#' @param forest_dataset `ForestDataset` R class
#' @param forest_num Index of the forest sample within the container
#' @return matrix of predictions with as many rows as in forest_dataset
#' and as many columns as samples in the `ForestContainer`
#' and as many columns as dimensions in the leaves of trees in `ForestContainer`
predict_raw_single_forest = function(forest_dataset, forest_num) {
stopifnot(!is.null(forest_dataset$data_ptr))
# Unpack dimensions
Expand All @@ -113,6 +113,21 @@ ForestSamples <- R6::R6Class(
return(output)
},

#' @description
#' Predict "raw" leaf values (without being multiplied by basis) for a specific tree in a specific forest on every observation in `forest_dataset`
#' @param forest_dataset `ForestDataset` R class
#' @param forest_num Index of the forest sample within the container
#' @param tree_num Index of the tree to be queried
#' @return matrix of predictions with as many rows as in `forest_dataset`
#' and as many columns as dimensions in the leaves of trees in `ForestContainer`
predict_raw_single_tree = function(forest_dataset, forest_num, tree_num) {
stopifnot(!is.null(forest_dataset$data_ptr))

# Predict leaf values from forest
output <- predict_forest_raw_single_tree_cpp(self$forest_container_ptr, forest_dataset$data_ptr, forest_num, tree_num)
return(output)
},

#' @description
#' Set a constant predicted value for every tree in the ensemble.
#' Stops program if any tree is more than a root node.
Expand Down
Loading