Fuzzy classification through generative multi-task learning

Han Liu*, Mihaela Cocea

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

Abstract

In this chapter, we introduce the concepts of both generative learning and multi-task learning, and presents a proposed fuzzy approach for multi-task classification. We also discuss the advantages of fuzzy classification in the context of generative multi-task learning, in comparison with traditional classification in the context of discriminative single-task learning.

Original languageEnglish
Title of host publicationGranular Computing Based Machine Learning
Subtitle of host publicationA Big Data Processing Approach
EditorsHan Liu, Mihaela Cocea
PublisherSpringer Nature
Pages37-47
Number of pages11
ISBN (Electronic)9783319700588
ISBN (Print)9783319700571, 9783319888842
DOIs
Publication statusPublished - 23 Nov 2017

Publication series

NameStudies in Big Data
Volume35
ISSN (Print)2197-6503
ISSN (Electronic)2197-6511

Keywords

  • Fuzzification Stage
  • Fuzzy Membership Degree
  • Fuzzy Rules
  • General Multi-task Learning
  • Mutual Exclusion

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