R/c_NGAS.R

In egenn/rtemis: Machine Learning and Visualization

# c_NGAS.R
# ::rtemis::
# 2016 E.D. Gennatas www.lambdamd.org

#' Neural Gas Clustering
#'
#' Perform [Neural Gas clustering](https://en.wikipedia.org/wiki/Neural_gas) using `flexclust::cclust`
#'
#' @inheritParams c_KMeans
#' @param x Input matrix / data.frame
#' @param k Integer: Number of clusters to get
#' @param dist Character: Distance measure to use: 'euclidean' or 'manhattan'
#' @param ... Additional parameters to be passed to `flexclust::cclust`
#' 
#' @author E.D. Gennatas
#' @return `rtClust` object
#' @family Clustering
#' @export

c_NGAS <- function(x, 
                   x.test = NULL,
                   k = 2,
                   dist = "euclidean",
                   verbose = TRUE, ...) {

  # Intro ----
  start.time <- intro(verbose = verbose)
  clust.name <- "NGAS"

  # Data ----
  if (is.null(colnames(x))) colnames(x) <- paste0("Feature_", seq_len(NCOL(x)))
  x <- as.data.frame(x)
  xnames <- colnames(x)

  # Dependencies ----
  dependency_check("flexclust")

  # Arguments ----
  if (missing(x)) {
    print(args(c_NGAS))
    stop("x is missing")
  }

  # NGAS ----
  if (verbose) msg2("Performing Neural Gas clustering with k = ", k, "...", sep = "")
  clust <- flexclust::cclust(x,
                             k = k,
                             dist = dist,
                             method = "neuralgas", ...)

  # Clusters ----
  clusters.train <- flexclust::clusters(clust)
  if (!is.null(x.test)) {
    clusters.test <- flexclust::clusters(clust, x.test)
  } else {
    clusters.test <- NULL
  }

  # Outro ----
  cl <- rtClust$new(clust.name = clust.name,
                    k = k,
                    xnames = xnames,
                    clust = clust,
                    clusters.train = clusters.train,
                    clusters.test = clusters.test,
                    parameters = list(k = k, dist = dist),
                    extra = list())
  outro(start.time, verbose = verbose)
  cl

} # rtemis::c_NGAS