Download JAR files tagged by international with all dependencies

racedIncrementalLogitBoost from group nz.ac.waikato.cms.weka (version 1.0.2)

Classifier for incremental learning of large datasets by way of racing logit-boosted committees. For more information see: Eibe Frank, Geoffrey Holmes, Richard Kirkby, Mark Hall: Racing committees for large datasets. In: Proceedings of the 5th International Conferenceon Discovery Science, 153-164, 2002.

Group: nz.ac.waikato.cms.weka Artifact: racedIncrementalLogitBoost
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Artifact racedIncrementalLogitBoost
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/racedIncrementalLogitBoost
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

naiveBayesTree from group nz.ac.waikato.cms.weka (version 1.0.2)

Class for generating a decision tree with naive Bayes classifiers at the leaves. For more information, see Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid. In: Second International Conference on Knoledge Discovery and Data Mining, 202-207, 1996.

Group: nz.ac.waikato.cms.weka Artifact: naiveBayesTree
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Artifact naiveBayesTree
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/naiveBayesTree
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

grading from group nz.ac.waikato.cms.weka (version 1.0.2)

Implements Grading. The base classifiers are "graded". For more information, see A.K. Seewald, J. Fuernkranz: An Evaluation of Grading Classifiers. In: Advances in Intelligent Data Analysis: 4th International Conference, Berlin/Heidelberg/New York/Tokyo, 115-124, 2001.

Group: nz.ac.waikato.cms.weka Artifact: grading
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Artifact grading
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/grading
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

citationKNN from group nz.ac.waikato.cms.weka (version 1.0.2)

Modified version of the Citation kNN multi instance classifier. For more information see: Jun Wang, Zucker, Jean-Daniel: Solving Multiple-Instance Problem: A Lazy Learning Approach. In: 17th International Conference on Machine Learning, 1119-1125, 2000.

Group: nz.ac.waikato.cms.weka Artifact: citationKNN
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Artifact citationKNN
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/citationKNN
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

CLOPE from group nz.ac.waikato.cms.weka (version 1.0.2)

Yiling Yang, Xudong Guan, Jinyuan You: CLOPE: a fast and effective clustering algorithm for transactional data. In: Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, 682-687, 2002.

Group: nz.ac.waikato.cms.weka Artifact: CLOPE
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Artifact CLOPE
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/CLOPE
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

optics_dbScan from group nz.ac.waikato.cms.weka (version 1.0.6)

The OPTICS and DBScan clustering algorithms. Martin Ester, Hans-Peter Kriegel, Joerg Sander, Xiaowei Xu: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise. In: Second International Conference on Knowledge Discovery and Data Mining, 226-231, 1996; Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, Joerg Sander: OPTICS: Ordering Points To Identify the Clustering Structure. In: ACM SIGMOD International Conference on Management of Data, 49-60, 1999.

Group: nz.ac.waikato.cms.weka Artifact: optics_dbScan
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Artifact optics_dbScan
Group nz.ac.waikato.cms.weka
Version 1.0.6
Last update 16. December 2019
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/optics_dbScan
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

beige-pdfwriter from group org.beigesoft (version 1.0.3)

This is light-weight (all JARs size is about 250KB), international friendly and fast PDF writer. You will not get performance problems on a high load server application, e.g. if hundred users push print (to PDF) button at the same time. It's cross-platform writer - Standard Java and Android. There are not 3-d party dependencies except Java, Android and TTF fonts.

Group: org.beigesoft Artifact: beige-pdfwriter
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Artifact beige-pdfwriter
Group org.beigesoft
Version 1.0.3
Last update 14. October 2019
Organization not specified
URL https://sites.google.com/site/beigesoftware
License BSD 2-Clause License
Dependencies amount 1
Dependencies beige-docwriter,
There are maybe transitive dependencies!

stackingC from group nz.ac.waikato.cms.weka (version 1.0.4)

Implements StackingC (more efficient version of stacking). For more information, see A.K. Seewald: How to Make Stacking Better and Faster While Also Taking Care of an Unknown Weakness. In: Nineteenth International Conference on Machine Learning, 554-561, 2002. Note: requires meta classifier to be a numeric prediction scheme

Group: nz.ac.waikato.cms.weka Artifact: stackingC
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Artifact stackingC
Group nz.ac.waikato.cms.weka
Version 1.0.4
Last update 19. November 2018
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/stackingC
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 1.0.6)

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.

Group: nz.ac.waikato.cms.weka Artifact: XMeans
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6 downloads

Artifact XMeans
Group nz.ac.waikato.cms.weka
Version 1.0.6
Last update 28. February 2018
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!

ensemblesOfNestedDichotomies from group nz.ac.waikato.cms.weka (version 1.0.6)

A meta classifier for handling multi-class datasets with 2-class classifiers by building an ensemble of nested dichotomies. For more info, check Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems. In: PKDD, 84-95, 2005. Eibe Frank, Stefan Kramer: Ensembles of nested dichotomies for multi-class problems. In: Twenty-first International Conference on Machine Learning, 2004.

Group: nz.ac.waikato.cms.weka Artifact: ensemblesOfNestedDichotomies
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Artifact ensemblesOfNestedDichotomies
Group nz.ac.waikato.cms.weka
Version 1.0.6
Last update 21. February 2017
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/ensemblesOfNestedDichotomies
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

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