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