clprofiles: profile k prototypes clustering

Description Usage Arguments Details Author(s) Examples

View source: R/kprototypes.R

Description

Visualization of k prototypes clustering result for cluster interpretation.

Usage

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clprofiles(object, x, vars = NULL,
  col = brewer.pal(max(unique(object$cluster)), "Set3"))

Arguments

object

Object resulting from a call of resulting kproto. Also other kmeans like objects with object$cluster and object$size are possible.

x

Original data.

vars

Vector of either coloumn indices or variable names.

col

Palette of cluster colours to be used for the plots.

Details

For numerical variables boxplots and for factor variables barplots of each cluster are generated.

Author(s)

[email protected]

Examples

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# generate toy data with factors and numerics

n   <- 100
prb <- 0.9
muk <- 1.5 
clusid <- rep(1:4, each = n)

x1 <- sample(c("A","B"), 2*n, replace = TRUE, prob = c(prb, 1-prb))
x1 <- c(x1, sample(c("A","B"), 2*n, replace = TRUE, prob = c(1-prb, prb)))
x1 <- as.factor(x1)

x2 <- sample(c("A","B"), 2*n, replace = TRUE, prob = c(prb, 1-prb))
x2 <- c(x2, sample(c("A","B"), 2*n, replace = TRUE, prob = c(1-prb, prb)))
x2 <- as.factor(x2)

x3 <- c(rnorm(n, mean = -muk), rnorm(n, mean = muk), rnorm(n, mean = -muk), rnorm(n, mean = muk))
x4 <- c(rnorm(n, mean = -muk), rnorm(n, mean = muk), rnorm(n, mean = -muk), rnorm(n, mean = muk))

x <- data.frame(x1,x2,x3,x4)

# apply k prototyps
kpres <- kproto(x, 4)
clprofiles(kpres, x)

# in real world  clusters are often not as clear cut
# by variation of lambda the emphasize is shifted towards factor / numeric variables    
kpres <- kproto(x, 2)
clprofiles(kpres, x)

kpres <- kproto(x, 2, lambda = 0.1)
clprofiles(kpres, x)

kpres <- kproto(x, 2, lambda = 25)
clprofiles(kpres, x)

clustMixType documentation built on Sept. 4, 2017, 5:03 p.m.