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#'PCA Plot of the Noise Score of Each Individual
#'
#' This function plots the noise score for each observation
#' @param score a vector of values indicating the optential of being a noise.
#' @param data matrix or data frame with no label.
#' @param cl factor of true classifications of data set.
#' @param geom.ind as geom for observations, which can be set to "text", "point" and "none". The default is "text".
#' @param labelsize size of geom_text.
#' @param geom_point_size size of geom_point and geom_none.
#' @param ... optional parameters to be passed to other methods.
#' @return an plot of PCA with the noise score of each observation
#' @author Wanwan Zheng
#' @import dplyr
#' @import FactoMineR
#' @import factoextra
#' @import ggplot2
#'
#' @examples
#'
#' data(iris)
#' out = fmf(Species~.,iris)
#' plot(out$noise_score, iris[,-1], iris[,1])
#'
#'@name plot
#'@export
plot = function(score,
data,
cl,
geom.ind = "text",
labelsize = 3,
geom_point_size = 3,
...)
{
dev.new()
pca.res = data %>% FactoMineR::PCA(graph = FALSE)
p = pca.res %>%
factoextra::fviz_pca_ind(geom.ind = geom.ind,
col.ind = score,
gradient.cols = c("#6495ed", "#ff8c00", "#ff0000"),
labelsize = labelsize,
legend.title = "Noise score")
p = p + geom_point(shape = as.numeric(cl),aes(colour = score),size = geom_point_size)
p
}
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