## NAMESPACE, IMPORTS
#' @importFrom randomForest randomForest
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#' @importFrom methods setClass setGeneric setMethod extends getClass is new prototype signature slot
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#' @import caret
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#' @import ggplot2
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#' @importFrom stats cor lowess predict quantile rbinom sd
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#' @importFrom utils tail head
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#'@import foreach
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#' @importFrom graphics boxplot
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## SUPPORTING FUNCTIONS
# get mode
Mode <- function(x) {
ux <- unique(x)
ux[which.max(tabulate(match(x, ux)))]}
# test for even/odd
is.odd <- function(x) x %% 2 != 0
# extract validation results
extract <- function(x){
row <- c(variance=x@variance, finite=x@finite, completeobs=x@completeobs, classbalance=x@classbalance, ntopratiotwoplus=x@ntopratiotwoplus, mindimensions=x@mindimensions)
}
## SUPPORTING ENVIRONMENT
#' environment for storing preprocessor definitions
#'
#' an environment to save and get the preprocessing technique function bodies. Note, this environment
#' is only created for function getpreprocessor(). \cr
#' @export
#' @keywords internal
preprocessordefinitionstorage <- new.env()
## SUPPORTING DATA
#' preprosim example
#'
#' examplesimulation <- preprosimrun(iris, fitmodels=FALSE) # 6561 contaminated data sets \cr
#' @format A PreprosimClass object
#' @keywords internal
"examplesimulation"
#' setgrid example
#'
#' Contaminated Iris-data preprocessed with 90 combinations. \cr
#' examplecombgrid <- setgrid(phases=c("imputation", "scaling", "smoothing"), data=contaminateddf) \cr
#' @format GridClass
"examplecombgrid"
#' preprocomb example
#'
#' Modified Iris-data preprocessed with 90 combinations and evaluated with \cr
#' svmRadial classifier and 400 times repreated holdout validation. \cr
#' @format ResultClass
"exampleresult"
#' metaheur example
#'
#' examplemetaheur <- metaheur(examplegrid, model="svmRadial", iterations = 30, nholdout = 400) \cr
#' @format A MetaheurClass object
#' @keywords internal
"examplemetaheur"
globalVariables(c("out", "Index", "value", "outlier"))
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