Performing HCPC on the columns (i.e. variables) instead of the rows (i.e. individuals) after (M)CA

Question

I would like to perform a HCPC on the columns of my dataset, after performing a CA. For some reason I also have to specify at the start, that all of my columns are of type 'factor', just to loop over them afterwards again and convert them to numeric. I don't know why exactly, because if I check the type of each column (without specifying them as factor) they appear to be numeric... When I don't load and convert the data like this, however, I get an error like the following:

Error in eigen(crossprod(t(X), t(X)), symmetric = TRUE) : infinite or missing values in 'x'

Could this be due to the fact that there are columns in my dataset that only contain 0's? If so, how come that it works perfectly fine by reading everything in first as factor and then converting it to numeric before applying the CA, instead of just performing the CA directly?

The original issue with the HCPC, then, is the following:

# read in data; 40 x 267 data frame
data_for_ca <- read.csv("./data/data_clean_CA_complete.csv",row.names=1,colClasses = c(rep('factor',267)))

# loop over first 267 columns, converting them to numeric
for(i in 1:267)
  data_for_ca[[i]] <- as.numeric(data_for_ca[[i]])

# perform CA
data.ca <- CA(data_for_ca,graph = F)

# perform HCPC for rows (i.e. individuals); up until here everything works just fine
data.hcpc <- HCPC(data.ca,graph = T)

# now I start having trouble

# perform HCPC for columns (i.e. variables); use their coordinates that are stocked in the CA-object that was created earlier
data.cols.hcpc <- HCPC(data.ca$col$coord,graph = T)

The code above shows me a dendrogram in the last case and even lets me cut it into clusters, but then I get the following error:

Error in catdes(data.clust, ncol(data.clust), proba = proba, row.w = res.sauv$call$row.w.init) : object 'data.clust' not found

It's worth noting that when I perform MCA on my data and try to perform HCPC on my columns in that case, I get the exact same error. Would anyone have any clue as how to fix this or what I am doing wrong exactly? For completeness I insert a screenshot of the upper-left corner of my dataset to show what it looks like:

Thanks in advance for any possible help!

Answer 1

I know this is old, but because I've been troubleshooting this problem for a while today:

HCPC says that it accepts a data frame, but any time I try to simply pass it $col$coord or $colcoord from a standard ca object, it returns this error. My best guess is that there's some metadata it actually needs/is looking for that isn't in a data frame of coordinates, but I can't figure out what that is or how to pass it in.

The current version of FactoMineR will actually just allow you to give HCPC the whole CA object and tell it whether to cluster the rows or columns. So your last line of code should be:

data.cols.hcpc <- HCPC(data.ca, cluster.CA = "columns", graph = T)