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Author Topic: Implement rapidminer k-means in Python  (Read 157 times)
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« on: April 21, 2014, 10:10:02 AM »

Hi All,
I have used Rapidminer k-means algorithm to cluster binary dataset. Following matrix is based on web page access('1' for access and '0' for not access). First column is a label to identify each user.
0,1,1,0,1,0,1,0,1,1,0
1,1,0,0,1,1,0,1,0,1,0
2,1,0,0,0,1,0,1,0,1,1
3,1,0,1,0,1,0,0,0,1,0
4,0,1,1,1,0,1,0,1,0,0
5,1,1,0,0,1,0,1,1,1,1
6,0,0,1,0,1,1,0,1,0,0
7,1,1,0,1,0,1,0,0,1,0
8,1,0,0,0,1,0,1,1,1,1
9,0,1,1,0,1,0,1,0,0,0

I want to get an output in the following format which I already got from rapid-miner.
0 - cluster_1
1 - cluster_0
2 - cluster_1
3 - cluster_3
.. - ....

Now I need to do the same process in Python? Is it possible to implement rapidminer k-means in Python
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Marius
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« Reply #1 on: April 22, 2014, 10:18:54 AM »

The easiest and recommended way would be to setup a RapidMiner Server, create a scoring process that assigns the cluster to a row in the same way as you depicted below, store that process on the server. Then you can export the process as a webservice that you can call from your Python code. That way you can send new data to the server via the webservice, and the server will deliver the desired data as the response of the webservice.

Best regards,
Marius
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