XMeans
- Former user (Deleted)
Package
weka.clusterers
Synopsis
Cluster data using the X-means algorithm.
X-Means is K-Means extended by an Improve-Structure part In this part of the algorithm the centers are attempted to be split in its region. The decision between the children of each center and itself is done comparing the BIC-values of the two structures.
For more information see:
Dan Pelleg, Andrew W. Moore: X-means: Extending K-means with Efficient Estimation of the Number of Clusters. In: Seventeenth International Conference on Machine Learning, 727-734, 2000.
Available in Weka 3.6.x - 3.7.1. Available via the package management system for Weka >= 3.7.2 (XMeans)
Options
The table below describes the options available for XMeans.
Option |
Description |
|---|---|
KDTree |
The KDTree to use. |
binValue |
Set the value that represents true in the new attributes. |
cutOffFactor |
the cut-off factor to use |
debugLevel |
The debug level to use. |
debugVectorsFile |
The file containing the debug vectors (only for debugging!). |
distanceF |
The distance function to use. |
inputCenterFile |
The file to read the list of centers from. |
maxIterations |
the maximum number of iterations to perform |
maxKMeans |
the maximum number of iterations to perform in KMeans |
maxKMeansForChildren |
the maximum number of iterations KMeans that is performed on the child centers |
maxNumClusters |
set maximum number of clusters |
minNumClusters |
set minimum number of clusters |
outputCenterFile |
The file to write the list of centers to. |
seed |
The random number seed to be used. |
useKDTree |
Whether to use the KDTree. |
Capabilities
The table below describes the capabilites of XMeans.
Capability |
Supported |
|---|---|
Class |
No class |
Attributes |
Missing values, Date attributes, Numeric attributes |
Min # of instances |
1 |