A dendrogram (or tree diagram) is a graph used to represent relationships in hierarchical clustering.
Questions tagged [dendrogram]
65 questions
81
votes
7 answers
Where to cut a dendrogram?
Hierarchical clustering can be represented by a dendrogram. Cutting a dendrogram at a certain level gives a set of clusters. Cutting at another level gives another set of clusters. How would you pick where to cut the dendrogram? Is there something…
Eduardas
- 2,389
38
votes
1 answer
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 on a dataframe of patient records (e.g. similar to…
Wouter
- 2,242
34
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3 answers
How to interpret the dendrogram of a hierarchical cluster analysis
Consider the R example below: plot( hclust(dist(USArrests), "ave") ) What exactly does the y-axis "Height" mean? Looking at North Carolina and California (rather on the left). Is California "closer" to North Carolina than Arizona? Can I make this…
Richi W
- 3,566
9
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3 answers
How to plot a fan (Polar) Dendrogram in R?
I'm referring to something like this: suggested dataset for showing a solutions: data(mtcars) plot(hclust(dist(mtcars)))
Tal Galili
- 22,224
7
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1 answer
A measure to describe the distribution of a dendrogram
Could anyone suggest some statistical measures to describe the distribution of a dendrogram? If I have two dendrograms, how could can I quantify their structural differences?
Eduardas
- 2,389
6
votes
4 answers
Anyone know of a simple dendrogram visualizer?
I've written a small hierarchical clustering algorithm (for better or for worse). I'd like a quick way of visualizing it, any tooling ideas?
Hans
- 163
5
votes
1 answer
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 violates the ultrametric property. The two methods are:…
jslefche
- 175
5
votes
1 answer
Purpose of dendrogram and hierarchical clustering
This is likely a very naive question. I've lately been reading about hierarchical clustering algorithms, and various discussions about how to interpret dendrograms or find optimal heights for cutting a dendrogram. I've also played around with some…
siler
- 51
5
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2 answers
How to specify K cluster in Hierarchical clustering with noisy data?
I'm new in Mining and Clustering and I wonder how to cut off the hierarchical clustering Dendrogram to obtain a specific number of clusters. The problem is here that the data is noisy and the SLINK algorithm consider these noises as a cluster and…
farzad
- 163
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4
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How to randomize the tips of a functional trait dendrogram?
I have generated a functional trait dendrogram using species x trait and plots x species matrices through dbFD in package FD . I want to randomize the tips of the trait dendrogram to check if community assembly of the trees in my study area is…
4
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1 answer
How to convert a dendrogram back into a distance matrix?
Example code: our_dist <- dist(USArrests[1:4,]) dend <- as.dendrogram(hclust(our_dist , "ave")) plot(dend ) I would now wish to have a "dend2dist" function which will turn dend back to our_dist. Of course, it is not possible to do in full (AFAIK),…
Tal Galili
- 22,224
4
votes
2 answers
Applying Ward's method for calculating linkage
For an assignment, I have used iPython to create the dendrogram below, using Ward's method and Euclidean distance, from the following data: $$a=(0,0)$$ $$b=(1,2)$$ $$c=(3,4)$$ $$d=(4,1)$$ $$e=(2,2)$$ where dist({a},{b,e}) = 2.88, and…
Harr
- 61
4
votes
1 answer
Dendrogram in Hybrid Hierarchical Clustering and Cut-off criterion (Calinski-Harabasz presently)
I have questions regarding the dendrogram and the cut-off related to hybrid hierarchical clustering performed on data, as depicted below and taken from this paper Questions regarding Panel A (dendrogram) The clustering itself is done using the…
Pugl
- 1,591
4
votes
1 answer
Community detection and modularity
I am reading the book "Network science" of Barabasi and in particular the chapter on community detection. If I understand correctly, modularity is a goodness factor of partition calculated by a certain algorithm: the greater the value of modularity…
oipo
- 213
4
votes
0 answers
A high cophenetic correlation coefficient but dendrogram seems bad
I have 2 results for the same dataset. One is hierarchical clustering using Ward's method and I got 0.75 cophenetic correlation coefficient. The second is average method and I got 0.91 cophenetic correlation coefficient. I used "euclidean distance"…
Emrah Bilgiç
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