29 votes

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 ...
  • 391
4 votes

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 ...
  • 1,085
3 votes

Applying Ward's method for calculating linkage

Having banged my head on the wall for the last 2 hours on this, I feel your pain. The result is the square root of the increase in within-cluster sum of squares (vs. cluster means), multiplied by $\...
3 votes
Accepted

Cophenetic distance matrix to a dendrogram

You can just recreate the plot using hclust on the cophenetic of the object, and it would get you what you want (the method used ...
  • 20.4k
2 votes

Where to cut a dendrogram?

Some academic paper is giving a precise answer to that problem, under some separation assumptions (stability/noise resilience) on the clusters of the flat partition. The coarse idea of the paper ...
  • 3,988
2 votes

How to interpret the numeric values for "height" in a dendrogram using Ward's clustering method

I'm going to, ahem, go out on a limb here, ahem, and guess that you built your tree via the hclust function in base R with ...
2 votes

Purpose of dendrogram and hierarchical clustering

What threshold would you use on the matrix approach? That is what (for single-linkage, the other linkages are much more interesting) the height is: a distance threshold. The hierarchical clustering ...
1 vote
Accepted

Dendrogram in Hybrid Hierarchical Clustering and Cut-off criterion (Calinski-Harabasz presently)

The clustering itself is done using the Euclidean Distance - however the dendrogram is depicted using the squared Euclidean Distance. They don't explain ... From the looks of the dendrogram one ...
  • 53.3k
1 vote

Do heights between branches in R's heatmap dendrogram reflect true distances?

With complete linkage, it is supposedly the maximum of the pairwise distances from one cluster to the other. With single it ...
1 vote

Centroid linkage clustering with hclust yields wrong dendrogram?

According to the book Introduction to Information Retrieval. Christopher D. Manning, Prabhakar Raghavan and Hinrich Schütze: centroid clustering is not monotonic. So-called inversions can occur: ...
1 vote

How to interpret the dendrogram of a hierarchical cluster analysis

The horizontal axis represents the clusters. The vertical scale on the dendrogram represent the distance or dissimilarity. Each joining (fusion) of two clusters is represented on the diagram by the ...
  • 11
1 vote
Accepted

How to interpret a hierarchical clustering dendrogram?

The higher branch is a cluster including all the genes that you can see below in that branch. The height of a node is the distance between the two subclusters/subbranches (how that distance is ...
  • 4,303
1 vote

Hierarchical clustering and Dendrogram interpretation

If you want to use your hierarchical chart to judge a good number of groups, then you can look at the height gap between splits, perhaps something like this. Bigger gaps might be seen as better and ...
  • 32.4k
1 vote

Hierarchical clustering and Dendrogram interpretation

The number of clusters problem is generally difficult and depends (as the problem of selecting a suitable clustering method) on the meaning of the data and the aim of clustering. Some methods produce ...
1 vote

Dendrogram: Hierachical Clustering on Text data

I've seen this kind of dendogram with data on customer complaints (short text) when i tried computing the agglomerative clustering procedure with other methods rather than the ward algorithm. Try ...
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1 vote
Accepted

R: What is the distance function equivalent for this formula?

By default cor will compute the Pearson correlation coefficient. Subtracted from $1$ this is know as the Pearson Distance.
  • 701
1 vote
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 ...
  • 53.3k
1 vote

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 ...
1 vote

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.
  • 7,943
1 vote

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 ...
  • 1,699
1 vote

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 ...
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 ...
  • 20.4k
1 vote

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. ...
  • 1,312

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