sIB
Package
weka.clusterers
Synopsis
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.
Options
The table below describes the options available for sIB.
Option |
Description |
|---|---|
debug |
If set to true, clusterer may output additional info to the console. |
maxIterations |
set maximum number of iterations (default 100) |
minChange |
set minimum number of changes (default 0) |
notUnifyNorm |
set whether to normalize each instance to a unify prior probability (eg. 1). |
numClusters |
set number of clusters (default 2) |
numRestarts |
set number of restarts (default 5) |
seed |
The random number seed to be used. |
Capabilities
The table below describes the capabilites of sIB.
Capability |
Supported |
|---|---|
Class |
No class |
Attributes |
Numeric attributes |
Min # of instances |
1 |