sIB (3.7)

Cluster data using the sequential information bottleneck algorithm. Note: only hard clustering scheme is supported

sIB assign for each instance the cluster that have the minimum cost/distance to the instance.The trade-off beta is set to infinite so 1/beta is zero.

For more information, see:

Noam Slonim, Nir Friedman, Naftali Tishby: Unsupervised document classification using sequential information maximization.

In: Proceedings of the 25th International ACM SIGIR Conference on Research and Development in Information Retrieval, 129-136, 2002.

(based on WEKA 3.7)

For further options, click the 'More' - button in the dialog.

All weka dialogs have a panel where you can specify classifier-specific parameters.

Input ports

1. Type: Table
   Training data
   Training data

Output ports

1. Type: Weka 3.7 Cluster
   Trained model
   Trained model