Download all versions of XMeans JAR files with all dependencies
XMeans from group nz.ac.waikato.cms.weka (version 1.0.6)
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.
Artifact XMeans
Group nz.ac.waikato.cms.weka
Version 1.0.6
Last update 28. February 2018
Tags: region using estimation comparing data centers children improve decision algorithm attempted center values more conference between itself seventeenth andrew information with structure pelleg done means international extended number learning machine structures clusters cluster moore split each part this extending efficient 2000
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/XMeans
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
Group nz.ac.waikato.cms.weka
Version 1.0.6
Last update 28. February 2018
Tags: region using estimation comparing data centers children improve decision algorithm attempted center values more conference between itself seventeenth andrew information with structure pelleg done means international extended number learning machine structures clusters cluster moore split each part this extending efficient 2000
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/XMeans
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
XMeans from group nz.ac.waikato.cms.weka (version 1.0.4)
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.
Artifact XMeans
Group nz.ac.waikato.cms.weka
Version 1.0.4
Last update 09. August 2013
Tags: region using estimation comparing data centers children improve decision algorithm attempted center values more conference between itself seventeenth andrew information with structure pelleg done means international extended number learning machine structures clusters cluster moore split each part this extending efficient 2000
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/XMeans
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
Group nz.ac.waikato.cms.weka
Version 1.0.4
Last update 09. August 2013
Tags: region using estimation comparing data centers children improve decision algorithm attempted center values more conference between itself seventeenth andrew information with structure pelleg done means international extended number learning machine structures clusters cluster moore split each part this extending efficient 2000
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/XMeans
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
XMeans from group nz.ac.waikato.cms.weka (version 1.0.3)
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.
Artifact XMeans
Group nz.ac.waikato.cms.weka
Version 1.0.3
Last update 26. April 2012
Tags: region using estimation comparing data centers children improve decision algorithm attempted center values more conference between itself seventeenth andrew information with structure pelleg done means international extended number learning machine structures clusters cluster moore split each part this extending efficient 2000
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/XMeans
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
Group nz.ac.waikato.cms.weka
Version 1.0.3
Last update 26. April 2012
Tags: region using estimation comparing data centers children improve decision algorithm attempted center values more conference between itself seventeenth andrew information with structure pelleg done means international extended number learning machine structures clusters cluster moore split each part this extending efficient 2000
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/XMeans
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
XMeans from group nz.ac.waikato.cms.weka (version 1.0.2)
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.
Artifact XMeans
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 24. April 2012
Tags: region using estimation comparing data centers children improve decision algorithm attempted center values more conference between itself seventeenth andrew information with structure pelleg done means international extended number learning machine structures clusters cluster moore split each part this extending efficient 2000
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/XMeans
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 24. April 2012
Tags: region using estimation comparing data centers children improve decision algorithm attempted center values more conference between itself seventeenth andrew information with structure pelleg done means international extended number learning machine structures clusters cluster moore split each part this extending efficient 2000
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/XMeans
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!
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