Due to recent updates, all users are required to create an Altair One account to login to the RapidMiner community. Click the Register button to create your account using the same email that you have previously used to login to the RapidMiner community. This will ensure that any previously created content will be synced to your Altair One account. Once you login, you will be asked to provide a username that identifies you to other Community users. Email us at Community with questions.
Simple process Q: Clustering with weights
villepohjanheim
Member Posts: 2 Contributor I
Hi all
A real rookie question here. I tried searching the forum, but maybe i just don't know the right words. So please bear with..
I'm attempting to do a simple k-means clustering in RM (4.5) with answers/rows weighted. As the operator doesn't provide such option, how should I go about this?
Thanks for all answers/links/suggestions
A real rookie question here. I tried searching the forum, but maybe i just don't know the right words. So please bear with..
I'm attempting to do a simple k-means clustering in RM (4.5) with answers/rows weighted. As the operator doesn't provide such option, how should I go about this?
Thanks for all answers/links/suggestions
Tagged:
0
Answers
currently KMeans does not support weighted examples. The only way to go is to insert each example multiple times. If an example is twice as often part of the example set as another, it has the doubled weight on the distance calculation. Of course this way is hmmm not really desireable, because the runtime will increase with number of examples...
For a great number of examples or arbitrary weights, the only real way to go would be to extend the operator. Either write it on your own, or get it done by us for little money.
Greetings,
Sebastian