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Cluster converges in exactly one iteration for any data set #14

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nishanthsiva opened this issue Apr 27, 2017 · 4 comments
Open

Cluster converges in exactly one iteration for any data set #14

nishanthsiva opened this issue Apr 27, 2017 · 4 comments

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@nishanthsiva
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Hi,

I am using your project for gene clustering and I found that the clustering result is always the same irrespective of the data set I use and the parameters I provide as input.

Used this data set with varying inflation rate and iterations. The clustering results hardly change. Is there any documentation or a set of examples that define how the clustering works? I am not sure if this problem is because of my data set or my lack of understanding of the algorithm.
examples.zip

@joandre
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joandre commented Apr 28, 2017

Hi,

Thanks for using MCL package. Can you give me an example of inflation and expansion rate you used with a code example ? Did you use released version or did you build the package from up-to-date code?

@evewurtele
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Sorry for slowness of reply, my student Nishanth graduated just then. We used up to date code. We are going back through the parameters and will provide info. Can you share any further updates that are not yet on github? Are there any publications? We find your code really useful. Thanks much :)

@joandre
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joandre commented Aug 12, 2017

No further updates right now, while I was waiting for an optimization of spark sparse matrix multiplication. But please take a look at akaltsikis repository : https://github.com/akaltsikis/Markov_Cluster_Algorithm.

@joandre
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joandre commented Aug 15, 2017

And no problem for the late answer. :-) Congratulations to Nishanth. Glad to see it was useful.

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