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#' Maxent
#'
#' This Class represents a MaxEnt model objects and hosts all the information
#' related to the model.
#'
#' @slot results matrix. The result that usually MaxEnt provide as a csv file.
#' @slot reg numeric. The value of the regularization multiplier used to train
#' the model.
#' @slot fc character. The feature class combination used to train the model.
#' @slot iter numeric. The number of iterations used to train the model.
#' @slot extra_args character. Extra arguments used to run MaxEnt.
#' @slot lambdas vector. The lambdas parameters of the model.
#' @slot coeff data.frame. The lambda coefficients of the model.
#' @slot formula formula. The formula used to make prediction.
#' @slot lpn numeric. Linear Predictor Normalizer.
#' @slot dn numeric. Density Normalizer.
#' @slot entropy numeric. The entropy value.
#' @slot min_max data.frame. The minimum and maximum values of the continuous
#' variables, used for clamping.
#'
#' @rdname Maxent-class
#' @export
#'
#' @author Sergio Vignali
Maxent <- setClass("Maxent",
slots = c(
results = "matrix",
reg = "numeric",
fc = "character",
iter = "numeric",
extra_args = "character",
lambdas = "vector",
coeff = "data.frame",
formula = "formula",
lpn = "numeric",
dn = "numeric",
entropy = "numeric",
min_max = "data.frame")
)
#' @param object Maxent object
#' @rdname Maxent-class
setMethod("show",
signature = "Maxent",
definition = function(object) {
cli::cli_h2("Object of class: {.cls {class(object)}}")
cli::cli_par()
cli::cli_text("Method: {.emph Maxent}")
cli::cli_end()
cli::cli_h3("Hyperparameters")
cli::cli_li("{.field reg}: {.val {object@reg}}")
cli::cli_li("{.field fc}: {.val {object@fc}}")
cli::cli_li("{.field iter}: {.val {object@iter}}")
})
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