I have a data which contain some NA value in their elements.
What I want to do is to **perform clustering without removing rows**
where the NA is present.
I understand that `gower` distance measure in `daisy` allow such situation.
But why my code below doesn't work?
__BEGIN__
# plot heat map with dendogram together.
library("gplots")
library("cluster")
# Arbitrarily assigning NA to some elements
mtcars[2,2] <- "NA"
mtcars[6,7] <- "NA"
mydata <- mtcars
hclustfunc <- function(x) hclust(x, method="complete")
# Initially I wanted to use this but it didn't take NA
#distfunc <- function(x) dist(x,method="euclidean")
# Try using daisy GOWER function
# which suppose to work with NA value
distfunc <- function(x) daisy(x,metric="gower")
d <- distfunc(mydata)
fit <- hclustfunc(d)
# Perform clustering heatmap
heatmap.2(as.matrix(mydata),dendrogram="row",trace="none",
margin=c(8,9), hclust=hclustfunc,distfun=distfunc);
__END__
The error message I got is this:
Error in which(is.na) : argument to 'which' is not logical
Calls: distfunc.g -> daisy
In addition: Warning messages:
1: In data.matrix(x) : NAs introduced by coercion
2: In data.matrix(x) : NAs introduced by coercion
3: In daisy(x, metric = "gower") :
binary variable(s) 8, 9 treated as interval scaled
Execution halted
At the end of the day, I'd like to perform hierarchical clustering
with the NA allowed data.
G.V.
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