How to Create a Dissimilarity Matrix with Daisy Function in R?
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)...
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
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