Download nz.ac.waikato.cms.weka.thirdparty JAR files with all dependencies
org.openide.awt from group com.github.veithen.visualwas.thirdparty (version 3.0.0)
Group: com.github.veithen.visualwas.thirdparty Artifact: org.openide.awt
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1 downloads
tabuAndScatterSearch from group nz.ac.waikato.cms.weka (version 1.0.2)
Search methods contributed by Adrian Pino (ScatterSearchV1, TabuSearch). ScatterSearch: Performs an Scatter Search through the space of attribute subsets. Start with a population of many significants and diverses subset stops when the result is higher than a given treshold or there's not more improvement. For more information see: Felix Garcia Lopez (2004). Solving feature subset selection problem by a Parallel Scatter Search. Elsevier. Tabu Search: Abdel-Rahman Hedar, Jue Wangy, Masao Fukushima (2006). Tabu Search for Attribute Reduction in Rough Set Theory.
Group: nz.ac.waikato.cms.weka Artifact: tabuAndScatterSearch
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webpagebytes-cms from group com.webpagebytes.cms (version 1.4)
A Java based CMS library for dynamic content.
weka-dev from group nz.ac.waikato.cms.weka (version 3.7.6)
The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This version represents the developer version, the
"bleeding edge" of development, you could say. New functionality gets added
to this version.
Group: nz.ac.waikato.cms.weka Artifact: weka-dev
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1 downloads
json from group com.jwebmp.thirdparty (version 0.67.0.2)
JSON is a light-weight, language independent, data interchange format.
See http://www.JSON.org/
The files in this package implement JSON encoders/decoders in Java.
It also includes the capability to convert between JSON and XML, HTTP
headers, Cookies, and CDL.
This is a reference implementation. There is a large number of JSON packages
in Java. Perhaps someday the Java community will standardize on one. Until
then, choose carefully.
The license includes this restriction: "The software shall be used for good,
not evil." If your conscience cannot live with that, then choose a different
package.
Group: com.jwebmp.thirdparty Artifact: json
There is no JAR file uploaded. A download is not possible! Please choose another version.
1 downloads
weka-dev from group nz.ac.waikato.cms.weka (version 3.7.9)
The Waikato Environment for Knowledge Analysis (WEKA), a machine
learning workbench. This version represents the developer version, the
"bleeding edge" of development, you could say. New functionality gets added
to this version.
Group: nz.ac.waikato.cms.weka Artifact: weka-dev
There is no JAR file uploaded. A download is not possible! Please choose another version.
1 downloads
consistencySubsetEval from group nz.ac.waikato.cms.weka (version 1.0.4)
Evaluates the worth of a subset of attributes by the level of consistency in the class values when the training instances are projected onto the subset of attributes. The consistency of any subset can never be lower than that of the full set of attributes, hence the usual practice is to use this subset evaluator in conjunction with a Random or Exhaustive search which looks for the smallest subset with consistency equal to that of the full set of attributes. See: H. Liu, R. Setiono: A probabilistic approach to feature selection - A filter solution. In: 13th International Conference on Machine Learning, 319-327, 1996.
1 downloads
ordinalClassClassifier from group nz.ac.waikato.cms.weka (version 1.0.5)
Meta classifier that allows standard classification algorithms to be applied to ordinal class problems.
For more information see:
Eibe Frank, Mark Hall: A Simple Approach to Ordinal Classification. In: 12th European Conference on Machine Learning, 145-156, 2001.
Robert E. Schapire, Peter Stone, David A. McAllester, Michael L. Littman, Janos A. Csirik: Modeling Auction Price Uncertainty Using Boosting-based Conditional Density Estimation. In: Machine Learning, Proceedings of the Nineteenth International Conference (ICML 2002), 546-553, 2002.
json from group com.jwebmp.thirdparty (version 0.67.0.4)
JSON is a light-weight, language independent, data interchange format.
See http://www.JSON.org/
The files in this package implement JSON encoders/decoders in Java.
It also includes the capability to convert between JSON and XML, HTTP
headers, Cookies, and CDL.
This is a reference implementation. There is a large number of JSON packages
in Java. Perhaps someday the Java community will standardize on one. Until
then, choose carefully.
The license includes this restriction: "The software shall be used for good,
not evil." If your conscience cannot live with that, then choose a different
package.
Group: com.jwebmp.thirdparty Artifact: json
There is no JAR file uploaded. A download is not possible! Please choose another version.
1 downloads
rsyntaxtextarea from group org.nuiton.thirdparty (version 1.4.1)
org.openide.windows from group com.github.veithen.visualwas.thirdparty (version 2.1.0)
Group: com.github.veithen.visualwas.thirdparty Artifact: org.openide.windows
There is no JAR file uploaded. A download is not possible! Please choose another version.
1 downloads
ilf-gpl from group net.sf.squirrel-sql.thirdparty-non-maven (version 1.6.1)
InfoNode Look and Feel is developed by NNL Technology AB. Visit
http://www.infonode.net for more information and the latest version of the library.
1 downloads
json from group com.jwebmp.thirdparty (version 0.67.0.1)
JSON is a light-weight, language independent, data interchange format.
See http://www.JSON.org/
The files in this package implement JSON encoders/decoders in Java.
It also includes the capability to convert between JSON and XML, HTTP
headers, Cookies, and CDL.
This is a reference implementation. There is a large number of JSON packages
in Java. Perhaps someday the Java community will standardize on one. Until
then, choose carefully.
The license includes this restriction: "The software shall be used for good,
not evil." If your conscience cannot live with that, then choose a different
package.
Group: com.jwebmp.thirdparty Artifact: json
There is no JAR file uploaded. A download is not possible! Please choose another version.
1 downloads
decorate from group nz.ac.waikato.cms.weka (version 1.0.2)
DECORATE is a meta-learner for building diverse ensembles of classifiers by using specially constructed artificial training examples. Comprehensive experiments have demonstrated that this technique is consistently more accurate than the base classifier, Bagging and Random Forests. Decorate also obtains higher accuracy than Boosting on small training sets, and achieves comparable performance on larger training sets. For more details see: P. Melville, R. J. Mooney: Constructing Diverse Classifier Ensembles Using Artificial Training Examples. In: Eighteenth International Joint Conference on Artificial Intelligence, 505-510, 2003; P. Melville, R. J. Mooney (2004). Creating Diversity in Ensembles Using Artificial Data. Information Fusion: Special Issue on Diversity in Multiclassifier Systems.
Group: nz.ac.waikato.cms.weka Artifact: decorate
There is no JAR file uploaded. A download is not possible! Please choose another version.
1 downloads
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.
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