Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/32929
Title: | On the generation of multi-label prototypes | Authors: | BELLO GARCIA, Marilyn NAPOLES RUIZ, Gonzalo VANHOOF, Koen Bello, Rafael |
Issue Date: | 2020 | Publisher: | Source: | Intelligent Data Analysis, 24 (S1) , p. 167 -183 | Abstract: | Data reduction techniques play a key role in instance-based classification to lower the amount of data to be processed. Prototype generation aims to obtain a reduced training set in order to obtain accurate results with less effort. This translates into a significant reduction in both algorithms' spatial and temporal burden. This issue is particularly relevant in multi-label classification , which is a generalization of multiclass classification that allows objects to belong to several classes simultaneously. Although this field is quite active in terms of learning algorithms, there is a lack of data reduction methods. In this paper, we propose several prototype generation methods from multi-label datasets based on Granular Computing. The simulations show that these methods significantly reduce the number of examples to a set of prototypes without significantly affecting classifiers' performance. | Keywords: | Multi-Label Classification;Prototype Generation;Granular Computing | Document URI: | http://hdl.handle.net/1942/32929 | ISSN: | 1088-467X | e-ISSN: | 1571-4128 | DOI: | 10.3233/IDA-200014 | ISI #: | 000599228700010 | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2022 |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
manuscript.pdf Restricted Access | Peer-reviewed author version | 1.72 MB | Adobe PDF | View/Open Request a copy |
WEB OF SCIENCETM
Citations
1
checked on Oct 14, 2024
Page view(s)
64
checked on Sep 6, 2022
Download(s)
8
checked on Sep 6, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.