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easyjasub-cmd from group com.github.riccardove.easyjasub (version 0.6.2)

Group: com.github.riccardove.easyjasub Artifact: easyjasub-cmd
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Artifact easyjasub-cmd
Group com.github.riccardove.easyjasub
Version 0.6.2
Last update 05. January 2015
Organization not specified
URL http://easyjasub.sourceforge.net
License not specified
Dependencies amount 3
Dependencies easyjasub-lib, commons-cli, nv-i18n,
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easyjasub-lib from group com.github.riccardove.easyjasub (version 0.6.2)

Group: com.github.riccardove.easyjasub Artifact: easyjasub-lib
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Artifact easyjasub-lib
Group com.github.riccardove.easyjasub
Version 0.6.2
Last update 05. January 2015
Organization not specified
URL http://easyjasub.sourceforge.net
License not specified
Dependencies amount 10
Dependencies antlr-runtime, rendersnake, commons-io, cssbox, html2image, subtitleConvert, kurikosu, lucene-analyzers-kuromoji, bdsup2sub-lib, stringtemplate,
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easyjasub from group com.github.riccardove.easyjasub (version 0.6.2)

Tool to assist in understanding Japanese subtitles those who have a little knowledge of Japanese language, for language learning. It allows you to get subtitles with furigana and in-line translation, in several formats suitable for both video rendering and self-study.

Group: com.github.riccardove.easyjasub Artifact: easyjasub
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Artifact easyjasub
Group com.github.riccardove.easyjasub
Version 0.6.2
Last update 05. January 2015
Organization Riccardo Vestrini
URL http://easyjasub.sourceforge.net
License The Apache Software License, Version 2.0
Dependencies amount 0
Dependencies No dependencies
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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
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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,
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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,
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rotationForest from group nz.ac.waikato.cms.weka (version 1.0.3)

An ensemble learning method inspired by bagging and random sub-spaces. Trains an ensemble of decision trees on random subspaces of the data, where each subspace has been transformed using principal components analysis.

Group: nz.ac.waikato.cms.weka Artifact: rotationForest
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Artifact rotationForest
Group nz.ac.waikato.cms.weka
Version 1.0.3
Last update 26. April 2012
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/rotationForest
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
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ordinalLearningMethod from group nz.ac.waikato.cms.weka (version 1.0.2)

An implementation of the Ordinal Learning Method (OLM). Further information regarding the algorithm and variants can be found in: Arie Ben-David (1992). Automatic Generation of Symbolic Multiattribute Ordinal Knowledge-Based DSSs: methodology and Applications. Decision Sciences. 23:1357-1372.

Group: nz.ac.waikato.cms.weka Artifact: ordinalLearningMethod
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Artifact ordinalLearningMethod
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/ordinalLearningMethod
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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1 downloads
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!

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

Nearest-neighbor-like algorithm using non-nested generalized exemplars (which are hyperrectangles that can be viewed as if-then rules). For more information, see Brent Martin (1995). Instance-Based learning: Nearest Neighbor With Generalization. Hamilton, New Zealand. Sylvain Roy (2002). Nearest Neighbor With Generalization. Christchurch, New Zealand.

Group: nz.ac.waikato.cms.weka Artifact: NNge
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Artifact NNge
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/NNge
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!

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

Class for building and using a Discriminative Multinomial Naive Bayes classifier. For more information see: Jiang Su,Harry Zhang,Charles X. Ling,Stan Matwin: Discriminative Parameter Learning for Bayesian Networks. In: ICML 2008', 2008.

Group: nz.ac.waikato.cms.weka Artifact: DMNBtext
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Artifact DMNBtext
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/DMNBtext
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
There are maybe transitive dependencies!



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