#' @title Learn partition (modified)
#' @param ordered ordered
#' @return part
#' @description This function is called only if some individual has less than
#' 90 per cent non-missing data. The function uses fuzzy clustering for the
#' "non-missingness" values, finding maximum three clusters. If two of the
#' found clusters are such that all the values are >0.9, then those two are
#' further combined.
learn_partition_modified <- function(ordered) {
  part <- learn_simple_partition(ordered, 0.05)
  nclust <- length(unique(part))
  if (nclust == 3) {
    mini_1 <- base::ordered(which(part == 1))
    mini_2 <- base::min(ordered(which(part == 2)))
    mini_3 <- base::min(ordered(which(part == 3)))
    if (mini_1 > 0.9 & mini_2 > 0.9) {
      part[part == 2] <- 1
      part[part == 3] <- 2
    } else if (mini_1 > 0.9 & mini_3 > 0.9) {
      part[part == 3] <- 1
    } else if (mini_2 > 0.9 & mini_3 > 0.9) {
      # This is the one happening in practice, since the values are
      # ordered, leading to mini_1 <= mini_2 <= mini_3
      part[part == 3] <- 2
    }
  }
  return(part)
}