I want to perform a cluster analysis with the pam function in R, using daisy to create a dissimilarity matrix. My data contains 2 columns (ID and Disease). Both are factors with a lot of values (400 and 1800 respectively). How can I create the dissimilarity matrix I need to cluster the data using pam?
Example data frame:
set.seed(1) df <- data.frame(ID = rep(sample(c("a","b","c","d","e","f","g"),10,replace = TRUE),70), disease = sample(c("flu","headache","pain","inflammation","depression","infection","chest pain"),100,replace = TRUE)) df <- unique(df) Can I run the daisy function on this data frame or do I have to convert it into another format?
1 Answer
Since "Dissimilarities will be computed between the rows of x" (?daisy), you may want to run daisy on the table of your data frame.
(df.tab <- table(df)) # disease # ID chest pain depression flu headache infection inflammation pain # a 1 1 1 1 1 1 1 # b 1 1 1 1 1 1 1 # c 1 1 0 0 1 1 1 # d 1 1 1 0 1 0 1 # e 0 1 1 1 1 1 0 # f 0 1 1 1 1 0 1 # g 1 1 1 1 1 1 0 library(cluster) daisy(df.tab, metric="euclidean") # Dissimilarities : # a b c d e f # b 0.000000 # c 1.414214 1.414214 # d 1.414214 1.414214 1.414214 # e 1.414214 1.414214 2.000000 2.000000 # f 1.414214 1.414214 2.000000 1.414214 1.414214 # g 1.000000 1.000000 1.732051 1.732051 1.000000 1.732051 # # Metric : euclidean # Number of objects : 7 
