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 |