The Resource Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods, by Sarah Vluymans, (electronic resource)

Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods, by Sarah Vluymans, (electronic resource)

Label
Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods
Title
Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods
Statement of responsibility
by Sarah Vluymans
Creator
Contributor
Author
Author
Provider
Subject
Language
eng
Summary
This book presents novel classification algorithms for four challenging prediction tasks, namely learning from imbalanced, semi-supervised, multi-instance and multi-label data. The methods are based on fuzzy rough set theory, a mathematical framework used to model uncertainty in data. The book makes two main contributions: helping readers gain a deeper understanding of the underlying mathematical theory; and developing new, intuitive and well-performing classification approaches. The authors bridge the gap between the theoretical proposals of the mathematical model and important challenges in machine learning. The intended readership of this book includes anyone interested in learning more about fuzzy rough set theory and how to use it in practical machine learning contexts. Although the core audience chiefly consists of mathematicians, computer scientists and engineers, the content will also be interesting and accessible to students and professionals from a range of other fields
Member of
http://library.link/vocab/creatorName
Vluymans, Sarah
http://bibfra.me/vocab/relation/httpidlocgovvocabularyrelatorsaut
OwJe8MW0uyE
Image bit depth
0
LC call number
Q342
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
SpringerLink
Series statement
Studies in Computational Intelligence,
Series volume
807
http://library.link/vocab/subjectName
  • Engineering
  • Artificial intelligence
  • Computational Intelligence
  • Artificial Intelligence
Label
Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods, by Sarah Vluymans, (electronic resource)
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Introduction -- Classification -- Understanding OWA based fuzzy rough sets -- Fuzzy rough set based classification of semi-supervised data -- Multi-instance learning -- Multi-label learning -- Conclusions and future work -- Bibliography
Dimensions
unknown
Extent
XVIII, 249 p. 23 illus., 10 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783030046637
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-030-04663-7
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-030-04663-7
Label
Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods, by Sarah Vluymans, (electronic resource)
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Introduction -- Classification -- Understanding OWA based fuzzy rough sets -- Fuzzy rough set based classification of semi-supervised data -- Multi-instance learning -- Multi-label learning -- Conclusions and future work -- Bibliography
Dimensions
unknown
Extent
XVIII, 249 p. 23 illus., 10 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783030046637
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-030-04663-7
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-030-04663-7

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