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#' @name predict_RF
#' @title preidict function for random forest objects in statTarget
#' @description Prediction of test data using random forest in statTarget.
#' @param object An object created by the function statTarget_rForest.
#' @param newdata A data frame or matrix containing new data. (Note: If not
#' given, the out-of-bag prediction in object is returned. see randomForest
#' package.
#' @param type One of response, prob. or votes, indicating the type of output:
#' predicted values, matrix of class probabilities, or matrix of vote counts.
#' class is allowed, but automatically converted to 'response', for backward
#' compatibility.
#' @param ... A generic predict function from randomForest package.
#' @return A class of predicted values is returned.
#' Object type is classification, for detail see randomForest package.
#' @usage predict_RF(object, newdata, type='response',...)
#' @examples
#' datpath <- system.file('extdata',package = 'statTarget')
#' statFile <- paste(datpath,'data_example.csv', sep='/')
#' getFile <- read.csv(statFile,header=TRUE)
#' rFtest <- rForest(getFile,ntree = 10,times = 5)
#' predictOutput <- predict_RF(rFtest, getFile[1:19,3:8])
#' @author Hemi Luan, hemi.luan@gmail.com
#' @seealso randomForest
#' @export
predict_RF <- function(object, newdata, type = "response", ...) {
# require(randomForest) need object from statTarget_rForest
if (!inherits(object$randomForest, "randomForest"))
stop("Object should be from statTarget_rForest")
newModel <- object$randomForest
output <- predict(newModel, newdata, type = "response", ...)
return(output)
}
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