Cluster of customer

Hello friends,
I need your help, I tell you that I am creating a customer segmentation. and between the data comes fields of type string atributes , which with the algorithms that used it is not possible to include this type of data.
in python you can include it with k-means but in knime using the same algorithm I

can’t. What algorithm or node should I use?

cyty | id customer | game name | state
|Coquimbo|10073 |Baccarat |Vitacura|
|Coquimbo|10118 |Tragamonedas |La Florida|
|Coquimbo|10544 |Tragamonedas |Antofagasta|
|Coquimbo|10525 |Hold’em Poker |Maipú|
|Coquimbo|10329 |Tragamonedas |Rancagua|

Hi you can use three algorithms which are:

  1. Expectation maximisation which is available in the Weka extension
  2. The Kmodes which is available in klaR package in the R extension
  3. The Kprototypes which is available in the clustMixType package in the R extension

I am attaching you a workflow that has both numerical and categorical information

Hope it helps


Kprototypes.knwf (3.2 MB)


thank you, very much i’m starting on this. I work for a casino in Chile. and I have a lot to learn

1 Like

Hi @andresfx_2000,
have you taken a look at the KNIME hub yet? There you can find example workflows for many applications, e.g. the following for customer segmentation (which is clustering customers):



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