Rule based systems for big data : a machine learning approach /: a machine learning approach. ([2015])
- Record Type:
- Book
- Title:
- Rule based systems for big data : a machine learning approach /: a machine learning approach. ([2015])
- Main Title:
- Rule based systems for big data : a machine learning approach
- Further Information:
- Note: Han Liu, Alexander Gegov, Mihaela Cocea.
- Authors:
- Liu, Han
Gegov, Alexander
Cocea, Mihaela - Contents:
- Introduction.- Theoretical Preliminaries.- Generation of Classification Rules.- Simplification of Classification Rules.- Representation of Classification Rules.- Ensemble Learning Approaches.- Interpretability Analysis.
- Publisher Details:
- Cham : Springer
- Publication Date:
- 2015
- Copyright Date:
- 2016
- Extent:
- 1 online resource (xiii, 121 pages), illustrations (some color)
- Subjects:
- 004.2/1
Engineering
System design
Rule-based programming
Machine learning
Big data
COMPUTERS -- Computer Literacy
COMPUTERS -- Computer Science
COMPUTERS -- Data Processing
COMPUTERS -- Hardware -- General
COMPUTERS -- Information Technology
COMPUTERS -- Machine Theory
COMPUTERS -- Reference
Big data
Machine learning
Rule-based programming
System design
Computers -- Intelligence (AI) & Semantics
Computers -- Database Management -- Data Mining
Artificial intelligence
Data mining
Artificial intelligence
Data mining
Electronic books - Languages:
- English
- ISBNs:
- 9783319236964
3319236962 - Related ISBNs:
- 9783319236957
3319236954 - Notes:
- Note: Includes bibliographical references.
Note: Online resource; title from PDF title page (SpringerLink, viewed September 16, 2015). - 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.372038
- Ingest File:
- 01_358.xml