# cache the default learners
#' @importFrom regressoR.functional FunctionalModel.defaultLearners
#' @importFrom regressoR.splines regressoR.spline.default
#' @importFrom regressoR.direct regressoR.direct.default
.default <- unlist(c(FunctionalModel.defaultLearners(),
regressoR.spline.default(),
regressoR.direct.default()),
recursive = TRUE);
# cache the monotonous learners
#' @importFrom regressoR.functional FunctionalModel.monotonousLearners
#' @importFrom regressoR.splines regressoR.spline.protected
#' @importFrom regressoR.direct regressoR.direct.default
.monotonous <- unlist(c(FunctionalModel.monotonousLearners(),
regressoR.spline.protected(),
regressoR.direct.default()),
recursive = TRUE);
#' @title Get the Default Learners for Regression of 2-Dimensional Data
#' @description Create the list of default learners for the use in
#' \code{\link{regressoR.applyLearners}}. These comprise some functional
#' models, some simple multi-layer perceptrons, and splines.
#' @return a list of regression learners that can be applied.
#' @export regressoR.defaultLearners
regressoR.defaultLearners <- function() .default
#' @title Get the Default Learners for Monotonous Regression of 2-Dimensional
#' Data
#' @description Create the list of default learners for monotonous models for
#' the use in \code{\link{regressoR.applyLearners}}. These comprise some
#' monotonous functional models, some simple restricted multi-layer
#' perceptrons, and bounded splines.
#' @return a list of regression learners that can be applied.
#' @export regressoR.monotonousLearners
regressoR.monotonousLearners <- function() .monotonous
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.