Nothing
#' @title Summary for combined random forests ensembles
#' @description summary method for combined random forests ensembles
#' @param object Object of class rf.ensembles
#' @param ... Ignored
#'
#' @method summary rf.ensembles
#'
#' @export
"summary.rf.ensembles" <- function(object, ...) {
cat("\nCall:\n", deparse(object$call), "\n")
cat(" Type of random forest: ", object$type, "\n", sep="")
cat(" Number of random forests models: ", object$nrf, "\n", sep="")
cat(" Number of trees: ", object$ntree, "\n",sep="")
cat("No. of variables tried at each split: ", object$mtry, "\n\n", sep="")
if(object$type == "classification") {
if(!is.null(object$confusion)) {
cat(" OOB estimate of error rate: ",
round(object$err.rate*100,2), "%\n", sep="")
cat("Confusion matrix:\n")
print(object$confusion)
if(!is.null(object$test$err.rate)) {
cat(" Test set error rate: ",
round(object$test$err.rate*100,2), "%\n", sep="")
cat("Confusion matrix:\n")
print(object$test$confusion)
}
}
}
if(object$type == "regression") {
if(!is.null(object$mse)) {
cat(" Mean of squared residuals: ", object$mse,
"\n", sep="")
cat(" % Var explained: ",
round(object$rsq, digits=2), "\n", sep="")
if(!is.null(object$test$mse)) {
cat(" Test set MSE: ",
round(object$test$mse, digits=2), "\n", sep="")
cat(" % Var explained: ",
round(object$test$rsq, digits=2), "\n", sep="")
}
}
if (!is.null(object$coefs)) {
cat(" Bias correction applied:\n")
cat(" Intercept: ", object$coefs[1], "\n")
cat(" Slope: ", object$coefs[2], "\n")
}
}
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.