Foundations and Advances in Data Mining

Studies in Fuzziness and Soft Computing 180

160,49 €
(inkl. MwSt.)
In den Warenkorb

Lieferbar innerhalb 1 - 2 Wochen

Bibliografische Daten
ISBN/EAN: 9783540250579
Sprache: Englisch
Umfang: x, 342 S.
Format (T/L/B): 2.5 x 24 x 16.4 cm
Auflage: 1. Auflage 2005
Einband: gebundenes Buch

Beschreibung

InhaltsangabeThe Mathematics of Learning.- Logical Regression Analysis: From Mathematical Formulas to Linguistic Rules.- A Feature/Attribute Theory for Association Mining and Constructing the Complete Feature Set.- A New Theoretical Framework for K-means-type Clustering.- Clustering via Decision Tree Construction.- Incremental Mining on Association Rules.- Mining Association Rules from Tabular Data Guided by Maximal Frequent Itemsets.- Sequential Pattern Mining by Pattern-Growth: Principles and Extensions.- Web Page Classification.- Web Mining - Concepts, Applications, and Research Directions.- Privacy-Preserving Data Mining.

Inhalt

The Mathematics of Learning.- Logical Regression Analysis: From Mathematical Formulas to Linguistic Rules.- A Feature/Attribute Theory for Association Mining and Constructing the Complete Feature Set.- A New Theoretical Framework for K-means-type Clustering.- Clustering via Decision Tree Construction.- Incremental Mining on Association Rules.- Mining Association Rules from Tabular Data Guided by Maximal Frequent Itemsets.- Sequential Pattern Mining by Pattern-Growth: Principles and Extensions.- Web Page Classification.- Web Mining - Concepts, Applications, and Research Directions.- Privacy-Preserving Data Mining.

Informationen gemäß Produktsicherheitsverordnung

Hersteller:
Springer Verlag GmbH
juergen.hartmann@springer.com
Tiergartenstr. 17
DE 69121 Heidelberg