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#' Predict function
#'
#' A custom predict function for FlexBoost
#'
#' This is a predict function of FlexBoost. FlexBoost consists of two predict functions.
#' One is built-in function in R and the other is this custom predict function for FlexBoost.
#' This custom predict function is needed for the calculation of the final strong classifier.
#' It returns the expected input data's labels.
#' @param object Tree information
#' @param X Variable of train data
#' @param type Class or probability
#' @param n_tree Number of trees
#' @examples
#' data <- read.csv(url("http://bit.ly/flex_iris"), TRUE)
#' model <- flex(data[,1:2], data[,6], 10, 0.1, 3, 2)
#' mnj.pred(model, data[,1:2], "response", NULL)
mnj.pred <- function(object, X, type = c("response", "prob"), n_tree = NULL){
# handle args
type <- match.arg(type)
if(is.null(n_tree)) { tree_seq <- seq_along(object$alphas) }
else { tree_seq <- seq(1, n_tree) }
# evaluate score function on sample
f <- 0
for(i in tree_seq){
tree <- object$trees[[i]]
tree$terms <- object$terms
pred <- as.integer(as.character(stats::predict(tree, data.frame(X), type = "class")))
f <- f + object$alphas[i] * pred
}
# handle response type
if(type == "response") { sign(f) }
else if(type == "prob") { 1/(1 + exp(-2 * f)) }
}
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