Granular-Relational Data Mining / Studies in Computational Intelligence Bd.702 (PDF)
How to Mine Relational Data in the Paradigm of Granular Computing?
(Sprache: Englisch)
This book provides two general granular computing approaches to mining relational data, the first of which uses abstract descriptions of relational objects to build their granular representation, while the second extends existing granular data mining...
sofort als Download lieferbar
Printausgabe 109.99 €
eBook (pdf) -10%
98.99 €
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenloser tolino webreader
Produktdetails
Produktinformationen zu „Granular-Relational Data Mining / Studies in Computational Intelligence Bd.702 (PDF)“
This book provides two general granular computing approaches to mining relational data, the first of which uses abstract descriptions of relational objects to build their granular representation, while the second extends existing granular data mining solutions to a relational case.
Both approaches make it possible to perform and improve popular data mining tasks such as classification, clustering, and association discovery. How can different relational data mining tasks best be unified? How can the construction process of relational patterns be simplified? How can richer knowledge from relational data be discovered? All these questions can be answered in the same way: by mining relational data in the paradigm of granular computing!
This book will allow readers with previous experience in the field of relational data mining to discover the many benefits of its granular perspective. In turn, those readers familiar with the paradigm of granular computing will find valuable insights on its application to mining relational data. Lastly, the book offers all readers interested in computational intelligence in the broader sense the opportunity to deepen their understanding of the newly emerging field granular-relational data mining.
Bibliographische Angaben
- Autor: Piotr Honko
- 2017, 1st ed. 2017, 123 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 3319527517
- ISBN-13: 9783319527512
- Erscheinungsdatum: 03.02.2017
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
eBook Informationen
- Dateiformat: PDF
- Größe: 1.73 MB
- Ohne Kopierschutz
- Vorlesefunktion
Sprache:
Englisch
Kommentar zu "Granular-Relational Data Mining / Studies in Computational Intelligence Bd.702"
Schreiben Sie einen Kommentar zu "Granular-Relational Data Mining / Studies in Computational Intelligence Bd.702".
Kommentar verfassen