All Downloads are FREE. Search and download functionalities are using the official Maven repository.

Download JAR files tagged by classification with all dependencies

Search JAR files by class name

classAssociationRules from group nz.ac.waikato.cms.weka (version 1.0.3)

Class association rules algorithms (including an implementation of the CBA algorithm). For more information see: W. Li, J. Han, J.Pei: CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules. In ICDM'01:369-376,2001. B. Liu, W. Hsu, Y. Ma: Integrating Classification and Association Rule Mining. In KDD'98:80-86,1998.

Group: nz.ac.waikato.cms.weka Artifact: classAssociationRules
Show all versions Show documentation Show source 
 

1 downloads
Artifact classAssociationRules
Group nz.ac.waikato.cms.weka
Version 1.0.3
Last update 29. July 2014
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/classAssociationRules
License GNU General Public License 3
Dependencies amount 2
Dependencies weka-dev, predictiveApriori,
There are maybe transitive dependencies!

parent from group net.sf.logdistiller (version 3)

LogDistiller is a logfile merge and sort tool. Log content is classified according to rules configured in an XML file. Classification results go into reports, which are published: simply stored in a file, sent by mail, or even added to a news feed.

Group: net.sf.logdistiller Artifact: parent
Show all versions 
There is no JAR file uploaded. A download is not possible! Please choose another version.
0 downloads
Artifact parent
Group net.sf.logdistiller
Version 3
Last update 08. May 2014
Organization not specified
URL http://logdistiller.sf.net/
License The Apache Software License, Version 2.0
Dependencies amount 0
Dependencies No dependencies
There are maybe transitive dependencies!

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

Classification by voting feature intervals. Intervals are constucted around each class for each attribute (basically discretization). Class counts are recorded for each interval on each attribute. Classification is by voting. For more info see: G. Demiroz, A. Guvenir: Classification by voting feature intervals. In: 9th European Conference on Machine Learning, 85-92, 1997.

Group: nz.ac.waikato.cms.weka Artifact: votingFeatureIntervals
Show all versions Show documentation Show source 
 

0 downloads
Artifact votingFeatureIntervals
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/votingFeatureIntervals
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

logdistiller from group net.sf.logdistiller (version 1.1)

Group: net.sf.logdistiller Artifact: logdistiller
Show all versions Show source 
 

0 downloads
Artifact logdistiller
Group net.sf.logdistiller
Version 1.1
Last update 29. November 2009
Organization not specified
URL Not specified
License not specified
Dependencies amount 5
Dependencies ant, mail, commons-io, commons-lang, jdom,
There are maybe transitive dependencies!

meka from group net.sf.meka (version 1.9.7)

The MEKA project provides an open source implementation of methods for multi-label classification and evaluation. It is based on the WEKA Machine Learning Toolkit. Several benchmark methods are also included, as well as the pruned sets and classifier chains methods, other methods from the scientific literature, and a wrapper to the MULAN framework.

Group: net.sf.meka Artifact: meka
Show all versions Show documentation Show source 
 

18 downloads
Artifact meka
Group net.sf.meka
Version 1.9.7
Last update 16. October 2022
Organization not specified
URL http://meka.sourceforge.net/
License GNU General Public License 3
Dependencies amount 13
Dependencies weka-dev, mulan, mst, flatlaf, jfilechooser-bookmarks, jclipboardhelper, jshell-scripting, jama, trove4j, bmad, autoencoder, markdownj-core, multisearch-weka-package,
There are maybe transitive dependencies!

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

Package for generating a single Extra-Tree. Use with the RandomCommittee meta classifier to generate an Extra-Trees forest for classification or regression. This classifier requires all predictors to be numeric. Missing values are not allowed. Instance weights are taken into account. For more information, see Pierre Geurts, Damien Ernst, Louis Wehenkel (2006). Extremely randomized trees. Machine Learning. 63(1):3-42.

Group: nz.ac.waikato.cms.weka Artifact: extraTrees
Show all versions Show documentation Show source 
 

0 downloads
Artifact extraTrees
Group nz.ac.waikato.cms.weka
Version 1.0.2
Last update 03. December 2017
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/extraTrees
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

org.apache.stanbol.enhancer.engine.topic from group org.apache.stanbol (version 1.0.0)

Implementation of an annotation engine that links the content item to a set of possible categories from a dedicated Solr index using MoreLikeThis queries. The classification can be either applied to a complete document (text in a given language) which is the default behavior or to a specific portion of the text (using a TextAnnotation).

Group: org.apache.stanbol Artifact: org.apache.stanbol.enhancer.engine.topic
Show all versions Show documentation Show source 
 

0 downloads
Artifact org.apache.stanbol.enhancer.engine.topic
Group org.apache.stanbol
Version 1.0.0
Last update 16. September 2016
Organization not specified
URL Not specified
License not specified
Dependencies amount 9
Dependencies commons-io, org.apache.felix.scr.annotations, rdf.core, slf4j-api, rdf.utils, org.apache.stanbol.entityhub.servicesapi, org.apache.stanbol.enhancer.servicesapi, org.apache.stanbol.commons.solr.managed, org.apache.stanbol.enhancer.engine.topic.api,
There are maybe transitive dependencies!

org.apache.stanbol.enhancer.engine.topic.api from group org.apache.stanbol (version 1.0.0)

Implementation of an annotation engine that links the content item to a set of possible categories from a dedicated Solr index using MoreLikeThis queries. The classification can be either applied to a complete document (text in a given language) which is the default behavior or to a specific portion of the text (using a TextAnnotation).

Group: org.apache.stanbol Artifact: org.apache.stanbol.enhancer.engine.topic.api
Show all versions Show documentation Show source 
 

0 downloads
Artifact org.apache.stanbol.enhancer.engine.topic.api
Group org.apache.stanbol
Version 1.0.0
Last update 16. September 2016
Organization not specified
URL Not specified
License not specified
Dependencies amount 2
Dependencies commons-lang, rdf.core,
There are maybe transitive dependencies!

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

Class implementing minimal cost-complexity pruning. Note when dealing with missing values, use "fractional instances" method instead of surrogate split method. For more information, see: Leo Breiman, Jerome H. Friedman, Richard A. Olshen, Charles J. Stone (1984). Classification and Regression Trees. Wadsworth International Group, Belmont, California.

Group: nz.ac.waikato.cms.weka Artifact: simpleCART
Show all versions Show documentation Show source 
 

9 downloads
Artifact simpleCART
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/simpleCART
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

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

Evaluates the worth of an attribute by using an SVM classifier. Attributes are ranked by the square of the weight assigned by the SVM. Attribute selection for multiclass problems is handled by ranking attributes for each class seperately using a one-vs-all method and then "dealing" from the top of each pile to give a final ranking. For more information see: I. Guyon, J. Weston, S. Barnhill, V. Vapnik (2002). Gene selection for cancer classification using support vector machines. Machine Learning. 46:389-422.

Group: nz.ac.waikato.cms.weka Artifact: SVMAttributeEval
Show all versions Show documentation Show source 
 

2 downloads
Artifact SVMAttributeEval
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/SVMAttributeEval
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!



Page 14 from 16 (items total 158)


© 2015 - 2024 Weber Informatics LLC | Privacy Policy