CODEWITHSUNDEEP
cluster-analysismatlabself-organizing-maps
Radon
Radon

Reputation: 31

Determining cluster membership in SOM (Self Organizing Map) for time series data

I am also working on a project that requires clustering of time series data. I am using the SOM toolbox that works in MATLAB for clustering purpose and stuck with the following problem: "How can we determine which data belongs to which cluster?" SOM randomly chooses data sample from dataset and finds BMU for each data sample. As far as I know, data sample identifier is not regarded as dimension of data in SOM algorithm. If it is the case then how can we track the samples? I don't think that som_bmus solves this issue. Any idea how you do it without changing any functions included in SOM toolbox?

Upvotes: 3

Views: 1315

Answers (2)

Piet93
Piet93

Reputation: 179

I know this is an old topic, but maybe still usefull for others.

Is your question on determining a what should be a cluster or is it which data belongs to which neuron? If it is the last I believe GulshanS has answered correctly but if it is on the question how you determine what is a cluster and what not it is still unanswered. You can do this with neighbor connections, dark regions mostly show 'walls' which is a break line for a cluster.

Cluster analysis is something different than what SOM does. SOM determines connections and assigns BMU which end up being a pre-determined grid with neurons. Multiple data inputs can belong to a neuron. Multiple neurons can belong to a cluster but these are not the output of SOM.

Upvotes: 0

GulshanS
GulshanS

Reputation: 9

y=vec2ind(output)

will give you the index number for the output generated by MATLAB.With this information,you can see which input data belongs to which neuron#.

Just use the above code directly in your script, it will do the rest.

Upvotes: 1

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