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.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.378372
- Ingest File:
- 02_359.xml