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bootstrap-select from group org.mvnpm (version 1.13.18)

The jQuery plugin that brings select elements into the 21st century with intuitive multiselection, searching, and much more. Now with Bootstrap 4 support.

Group: org.mvnpm Artifact: bootstrap-select
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Artifact bootstrap-select
Group org.mvnpm
Version 1.13.18
Last update 10. October 2023
Organization Casey Holzer
URL https://developer.snapappointments.com/bootstrap-select
License MIT
Dependencies amount 0
Dependencies No dependencies
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multiInstanceFilters from group nz.ac.waikato.cms.weka (version 1.0.10)

A collection of filters for manipulating multi-instance data. Includes PropositionalToMultiInstance, MultiInstanceToPropositional, MILESFilter and RELAGGS. For more information see: M.-A. Krogel, S. Wrobel: Facets of Aggregation Approaches to Propositionalization. In: Work-in-Progress Track at the Thirteenth International Conference on Inductive Logic Programming (ILP), 2003. Y. Chen, J. Bi, J.Z. Wang (2006). MILES: Multiple-instance learning via embedded instance selection. IEEE PAMI. 28(12):1931-1947. James Foulds, Eibe Frank: Revisiting multiple-instance learning via embedded instance selection. In: 21st Australasian Joint Conference on Artificial Intelligence, 300-310, 2008.

Group: nz.ac.waikato.cms.weka Artifact: multiInstanceFilters
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Artifact multiInstanceFilters
Group nz.ac.waikato.cms.weka
Version 1.0.10
Last update 23. November 2018
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/multiInstanceFilters
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
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DTNB from group nz.ac.waikato.cms.weka (version 1.0.3)

Class for building and using a decision table/naive bayes hybrid classifier. At each point in the search, the algorithm evaluates the merit of dividing the attributes into two disjoint subsets: one for the decision table, the other for naive Bayes. A forward selection search is used, where at each step, selected attributes are modeled by naive Bayes and the remainder by the decision table, and all attributes are modelled by the decision table initially. At each step, the algorithm also considers dropping an attribute entirely from the model. For more information, see: Mark Hall, Eibe Frank: Combining Naive Bayes and Decision Tables. In: Proceedings of the 21st Florida Artificial Intelligence Society Conference (FLAIRS), 318-319, 2008.

Group: nz.ac.waikato.cms.weka Artifact: DTNB
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Artifact DTNB
Group nz.ac.waikato.cms.weka
Version 1.0.3
Last update 30. April 2014
Organization University of Waikato, Hamilton, NZ
URL http://weka.sourceforge.net/doc.packages/DTNB
License GNU General Public License 3
Dependencies amount 1
Dependencies weka-dev,
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