# Tag Info

### How to interpret the dendrogram of a hierarchical cluster analysis

I had the same questions when I tried learning hierarchical clustering and I found the following pdf to be very very useful. http://www.econ.upf.edu/~michael/stanford/maeb7.pdf Even if Richard is ...
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### Community detection and modularity

Here are some answers to the multiple questions in your post (which I would avoid in the future- better answers will come with clear, individual questions). Which algorithm is more efficient? Perhaps ...
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Accepted

### Hierarchical clustering in R - centroid linkage - problem with dendrogram heights

Explaining calculations done in centroid linkage hierarchical clustering Your data: 5 points in 1D feature space: a 1 b 2 c 6 d 11 e 16 Compute ...
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### Hierachical cluster analysis of ordinal variables?

HAC needs a dissimilarity matrix. Compute the matrix as required for your application, e g., using rank correlation.
1 vote
Accepted

### Distance between two clusters

You have your distance definitions mixed up. $$d_{\max}(x,y) := \max_d |x_d-y_d|$$ is the maximum norm for vectors. What you need for complete linkage is a different kind of distance, one that is ...
1 vote
Accepted

### Dendrogram from table with repeated lines

Whereas the example you provide uses a distance matrix between all observations dist(as.matrix(mtcars)), you currently have a matrix of raw data, which is not ...
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### Would anyone be able to help me interpret the dendrogram in the picture?

A dendrogram that looks like this indicates essentially that the clustering failed. Well, of course the algorithm did not fail (or you wouldn't have a result), but there are no well-defined clusters. ...
1 vote

### Cluster similarity matrix as energies

A popular method that extends metric Multi-dimensional Scaling (MDS) is the ISOMAP algorithm. Per your comment, this is available in scikit learn as well.
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### Cluster similarity matrix as energies

I think you are muddling two things that should not be muddled. However, there are tools that will do the two things you want and visualise them concurrently. These are graph visualisation tools that ...
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### Cluster similarity matrix as energies

The standard approach to do this is by using multidimensional scaling (MDS). Depending on your data, you may be able to use metric MDS, or only non-metric MDS. On the other hand, "attactive/...
1 vote

### Get k most diverse objects from dendrogram (hierarchical clustering)

I would say that if you're looking for the truly optimal solution then no, a dendogram won't help. However, it may give you some decent heuristics. There's a mismatch between what you dendogram ...
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1 vote
Accepted

### How to plot a fan (Polar) Dendrogram in R?

Four years later, I am now able to answer this question. It can be done by combining two new packages: circlize and dendextend. The plot can be made using the ...
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### Where to cut a dendrogram?

As the other answers said, it is definitely subjective and dependent on what type of granularity you are trying to study. For a general approach, I cut this one to give me 2 clusters and 1 outlier. ...
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