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.

Evaluate a cosine-measure Clustering by Davies Bouldin

siamak_wantsiamak_want Member Posts: 98 Contributor II
edited July 2019 in Help
Hi all,

I am running a process which contains a k-means operator with "cosine similarity measure". and I want to evaluate it with a "cluster distance performance" operator with "Davies Bouldin" measure. As far as I know, the Davies bouldin measure is calculated by "Eucledian distance" measure, But my cluster model has been built upon a "cosine similarity measure". SO how can I evaluate a cosine-based k-means? Any idea please?

Tagged:

Answers

  • siamak_wantsiamak_want Member Posts: 98 Contributor II
    Any explanation or idea please?
  • awchisholmawchisholm RapidMiner Certified Expert, Member Posts: 458 Unicorn
    Hello

    I had a look at the code. I think it's this source file: CentroidBasedEvaluator.java 
    private double getDaviesBouldin(CentroidClusterModel model, ExampleSet exampleSet) throws OperatorException {
    		DistanceMeasure measure = new EuclideanDistance();
    I think you would have to write some Java to change how it works.

    regards

    Andrew
Sign In or Register to comment.