Linked Questions

0
votes
1answer
4k views

hclust analyse methods, R [duplicate]

I use currently the function hclust() for Dendogram in R. It looks like: res.hc <- hclust(d, method = "ward.D2" ) My special interest is to understand, what ...
1
vote
1answer
646 views

Choosing Distance function and Linkage in hierarchical clustering [duplicate]

I'm using Hierarchical Clustering Package in Mathematica to analyse the set of experimental data (each experimental point has about 10 parameters). There are a lot of options for Distance function and ...
1
vote
0answers
16 views

Intuition-building examples to help choose the right linkage method in hierarchical clustering [duplicate]

I'm currently reading An Introduction to Statistical Learning with Applications in R by Hastie & Tibshirani. In their discussion on the hierarchical clustering algorithm, they note that the notion ...
35
votes
3answers
21k views

How to select a clustering method? How to validate a cluster solution (to warrant the method choice)?

One of the biggest issue with cluster analysis is that we may happen to have to derive different conclusion when base on different clustering methods used (including different linkage methods in ...
34
votes
2answers
25k views

Hierarchical clustering with mixed type data - what distance/similarity to use?

In my dataset we have both continuous and naturally discrete variables. I want to know whether we can do hierarchical clustering using both type of variables. And if yes, what distance measure is ...
29
votes
1answer
18k views

Comparing hierarchical clustering dendrograms obtained by different distances & methods

[The initial title "Measurement of similarity for hierarchical clustering trees" was later changed by @ttnphns to better reflect the topic] I am performing a number of hierarchical cluster analyses ...
16
votes
3answers
29k views

What algorithm does ward.D in hclust() implement if it is not Ward's criterion?

The one used by option "ward.D" (equivalent to the only Ward option "ward" in R versions <= 3.0.3) does not implement Ward's (1963) clustering criterion, whereas option "ward.D2" implements ...
19
votes
4answers
6k views

With categorical data, can there be clusters without the variables being related?

When trying to explain cluster analyses, it is common for people to misunderstand the process as being related to whether the variables are correlated. One way to get people past that confusion is a ...
10
votes
3answers
6k views

Methods of initializing K-means clustering

I am interested in the current state of the art for selecting initial seeds (cluster centers) for K-means. Googling leads to two popular choices: random selection of initial seeds, and, using the ...
10
votes
1answer
14k views

What is the optimal distance function for individuals when attributes are nominal?

I do not know which distance function between individuals to use in case of nominal (unordered categorical) attributes. I was reading some textbook and they suggest Simple Matching function but some ...
5
votes
2answers
11k views

Gower's (dis)similarity index

I would like to ask a question about Gower similarity/dissimilarity index. Is it ok to use the Gower dissimilarity measure with Ward linkage clustering? I was reading that the Gower similarity index ...
6
votes
5answers
2k views

Clustering of variables: but they are mixed type, some are numeric, some are categorical

I have a dataset with 15 variables. Some variables are numeric, continuous. Other variables are boolean, dichotomous (true/false). There's also one variable categorical, nominal. ...
4
votes
1answer
1k views

Cluster analysis in R produces reversals on dendrogram

I'm attempting to perform hierarchical agglomerative cluster analysis in R. However, when I use particular clustering methods, I get reversals (upward branching) in the resulting tree, which ...
2
votes
2answers
1k views

How to assign existing cluster numbers for future data, using hierarchical clustering algorithms?

Assume we have some good clusters from some clustering algorithm and we want to assign the cluster numbers (labels) to future data (= to enrol new data points into the existing clusters, if to word it ...
0
votes
2answers
1k views

Creating clusters for binary data

I have a set of data with patients and their diseases. I would like to use hierarchical clustering or some kind of cluster analysis to make a dendrogram to see which diseases cluster together in this ...

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