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#' Storage class for the description of hyperoverlaps
#'
#' @slot entity1 A length-one character vector
#' @slot entity2 A length-one character vector
#' @slot dimensions A length n character vector containing the variables used to define the space
#' @slot occurrences A matrix containing the labelled input data
#' @slot shape shape of the decision boundary; either "linear" or "curvilinear"
#' @slot polynomial.order a length-one numeric vector showing the polynomial order of the most accurate kernel function. "0" if linear kernel.
#' @slot result a length-one character vector, either "overlap" or "non-overlap"
#' @slot accuracy a 2x2 table with the true (y) and predicted (pred) labels
#' @slot number.of.points.misclassified a length-one numeric vector
#' @slot model svm model used to plot decision boundary
#'
#' @name hyperoverlap-class
#' @rdname hyperoverlap-class
setOldClass("svm.formula")
methods::setClass(Class="Hyperoverlap",
methods::representation(
entity1="character",
entity2="character",
dimensions="character",
occurrences = "data.frame",
shape="character",
polynomial.order = "numeric",
result = "character",
accuracy = "table",
number.of.points.misclassified = "numeric",
model = "svm.formula"
)
)
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