About Implementing or proceeding with the new distance measure for Simple K-means Algorithm

classic Classic list List threaded Threaded
1 message Options
Reply | Threaded
Open this post in threaded view
|

About Implementing or proceeding with the new distance measure for Simple K-means Algorithm

Ajinkya Indulkar
Hello Everyone, as we know that to group the data instances in the cluster, we use similarity measure, and the most popular similarity measure is the euclidean distance metric. so in the Simple K-means Algorithm of the weka software, I am trying to use the similarity measure of the Gravitational Clustering Algorithm which is F = G* (m1 *m2) /d^2. 
Here F stands for the force which will be the distance measure. The G is gravitational constant, m1 and m2 are the two data instances, and the d is the euclidean distance between two instances. For a long I am trying to figure out how can I fit this equation in the weka, to find some results. If anyone can help me proceed with this, it would be a great help.

Sincerely,
Ajinkya

_______________________________________________
Wekalist mailing list -- [hidden email]
Send posts to [hidden email]
To unsubscribe send an email to [hidden email]
To subscribe, unsubscribe, etc., visit https://list.waikato.ac.nz/postorius/lists/wekalist.list.waikato.ac.nz
List etiquette: http://www.cs.waikato.ac.nz/~ml/weka/mailinglist_etiquette.html