Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering

Israël César Lerman

ISBN 10: 1447167910 / ISBN 13: 9781447167914

Published by Springer, 2016

About this Item

Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering | Israël César Lerman | Buch | xxiv | Englisch | 2016 | Springer | EAN 9781447167914 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Seller Inventory # 104114938

Bibliographic Details

• Title: Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering
• Publisher: Springer
• Publication Date: 2016
• Language: English
• ISBN 10: 1447167910
• ISBN 13: 9781447167914
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 42D millimeters 241 millimeters width by 160 millimeters height by 42 millimeters depth
• Weight: 1162 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This book offers an original and broad exploration of the fundamental methods in Clustering and Combinatorial Data Analysis, presenting new formulations and ideas within this very active field.

With extensive introductions, formal and mathematical developments and real case studies, this book provides readers with a deeper understanding of the mutual relationships between these methods, which are clearly expressed with respect to three facets: logical, combinatorial  and  statistical.

Using relational mathematical representation, all types of data structures can be handled in precise and unified ways which the author highlights in three stages:

• Clustering a set of descriptive attributes
• Clustering a set of objects or a set of object categories
• Establishing correspondence between these two dual clusterings

Tools for interpreting the reasons of a given cluster or clustering are also included.

Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering will be a valuable resource for students and researchers who are interested in the areas of Data Analysis, Clustering, Data Mining and Knowledge Discovery.