Dealing with imbalanced and weakly labelled data in machine learning using fuzzy and rough set methods. ([2019])

Record Type:: Book
Title:: Dealing with imbalanced and weakly labelled data in machine learning using fuzzy and rough set methods. ([2019])
Main Title:: Dealing with imbalanced and weakly labelled data in machine learning using fuzzy and rough set methods
Further Information:: Note: Sarah Vluymans.
Authors:: Vluymans, Sarah
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.
Publisher Details:: Cham, Switzerland : Springer
Publication Date:: 2019
Extent:: 1 online resource
Subjects:: 511.3/223
Fuzzy sets
Languages:: English
ISBNs:: 9783030046637
Related ISBNs:: 303004663X
3030046621
9783030046620
Notes:: Note: Description based on online resource; title from digital title page (viewed on February 14, 2019).
Access Rights:: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
Access Usage:: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
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Physical Locations:: British Library HMNTS - ELD.DS.378372
Ingest File:: 02_359.xml