Cluster analysis with daisy

Question

I'm trying to perform a Hierarchical cluster analysis with RStudio, by using the package daisy. This is my dataset:

data.frame':341 obs. of  28 variables:
$ Impo_Env : Ord.factor w/ 3 levels "Low"<"Med"<"High": 3 2 3 2 3 2 3 3 2 3 ...
$ ComparativePriority_IAS: Ord.factor w/ 3 levels "Low"<"Med"<"High": 3 1 3 2 3 2 3 2 3 2 ...
$ Strategy_Eradication: Ord.factor w/ 3 levels "No intervention"<..: 3 2 3 2 3 2 3 2 2 3 ...
$ Knowl_BiodivLoss: Factor w/ 2 levels "0","1": 2 1 2 2 2 1 2 2 2 2 ...
$ Control_Trade: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ...
$ Engagement_Retail: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ...
$ Knowl_PastProj: Factor w/ 2 levels "0","1": 1 1 1 1 2 1 1 1 2 1 ...
$ Priority_IAS: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ...
$ Knowl_Eradic: Factor w/ 2 levels "0","1": 2 1 2 1 2 2 1 2 2 1 ...
$ Alert_CFS: Factor w/ 2 levels "0","1": 1 2 1 2 1 2 2 1 2 1 ...
$ Alert_Municipality: Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 1 ...
$ Alert_Park: Factor w/ 2 levels "0","1": 2 1 2 1 2 1 1 2 1 1 ...
$ Alert_Police: Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 1 ...
$ Alert_Firemen: Factor w/ 2 levels "0","1": 1 1 1 1 1 1 1 1 1 2 ...
$ Supp_AuthorityIAS: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ...
$ Knowl_Env: Factor w/ 2 levels "0","1": 2 1 2 2 2 2 2 2 2 2 ...
$ Info_Tv: Factor w/ 2 levels "0","1": 2 2 1 2 2 2 2 1 2 1 ...
$ Info_Web: Factor w/ 2 levels "0","1": 2 1 2 2 2 1 2 1 2 2 ...
$ Info_Radio: Factor w/ 2 levels "0","1": 1 1 1 1 1 2 1 2 1 1 ...
$ Info_Magazines: Factor w/ 2 levels "0","1": 1 1 2 1 2 1 1 2 1 1 ...
$ Info_School: Factor w/ 2 levels "0","1": 1 1 2 1 1 1 1 1 1 2 ...
$ Blacklist: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ...
$ Workshop: Factor w/ 2 levels "0","1": 1 1 2 1 2 1 2 2 1 1 ...
$ SuppFin_FutProj: Factor w/ 2 levels "0","1": 2 1 2 1 2 2 2 2 2 2 ...
$ Tourist_dummy: Factor w/ 2 levels "0","1": 1 1 1 2 2 1 1 1 2 1 ...
$ Gender: Factor w/ 2 levels "Female","Male": 1 2 1 2 1 1 2 2 2 1 ...
$ logIASknown: num  2.89 2.94 2.89 2.56 3.14 ...
$ Age: int  20 41 14 10 26 33 19 59 23 16 ...

I would like to use the Euclidean distance with daisy, however when I run

daisy(fuu, metric = c("euclidean"), type=list(ordratio = c(1,2,3), asymm=c(4:24), symm=c(25,26)))

The output is not fine. Gower's distance is used instead of Euclidean distance:

Warning message:In daisy(fuu, metric = c("euclidean"), type = list(ordratio = c(1,:with mixed variables, metric "gower" is used automatically

How can I fix it?

Answer 1

As described in "Details" section within the documentation of the daisy function contained in the cluster package:

The handling of nominal, ordinal, and (a)symmetric binary data is achieved by using the general dissimilarity coefficient of Gower (1971). If x contains any columns of these data-types, both arguments metric and stand will be ignored and Gower's coefficient will be used as the metric.

In other words, for euclidean metrics (distances as root sum-of-squares of differences) to be computed, input columns must be numeric (mode) variables (i.e. all columns when x is a matrix) and thus recognised as interval scaled variables, as opposed to nominal (columns of class factor) variables or ordinal (columns of class ordered) variables. Specifying variable type within the type argument does not change this fact.

Under these premises, and supposing it makes sense for all of your 28 variables despite some being qualitative binary, you might try converting them with as.numeric and proceed then, reason being: with mixed variables metric "gower" overrides being automatically used.