Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering
Authors: Lerman, Israël César
Free Preview- Offers a step-by-step process of the path of the data to the synthetic structure summarizing the data given by a hierarchical or non-hierarchical clustering
- Presents brand new principles and methods within the Data Mining field
- Examines ascendant agglomerative hierarchical clustering and Likelihood Linkage Analysis (LLA) clustering methods from metrical, algorithmic and computational aspects
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- About this book
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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.
- Reviews
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“This book provides a synthetic and systematic presentation of clustering, combinatorial, and statistical data analysis. … the presentation is interesting and original. Keeping a smart balance between theoretical concepts and practical issues, the book is addressed to students and researchers interested in data mining, data analysis, and clustering.” (Florin Gorunescu, zbMATH 1338.62012, 2016)
- Table of contents (12 chapters)
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On Some Facets of the Partition Set of a Finite Set
Pages 1-59
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Two Methods of Non-hierarchical Clustering
Pages 61-99
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Structure and Mathematical Representation of Data
Pages 101-148
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Ordinal and Metrical Analysis of the Resemblance Notion
Pages 149-197
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Comparing Attributes by Probabilistic and Statistical Association I
Pages 199-249
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Table of contents (12 chapters)
- Download Preface 1 PDF (90.3 KB)
- Download Sample pages 2 PDF (405.5 KB)
- Download Table of contents PDF (270.8 KB)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering
- Authors
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- Israël César Lerman
- Series Title
- Advanced Information and Knowledge Processing
- Copyright
- 2016
- Publisher
- Springer-Verlag London
- Copyright Holder
- Springer-Verlag London
- eBook ISBN
- 978-1-4471-6793-8
- DOI
- 10.1007/978-1-4471-6793-8
- Hardcover ISBN
- 978-1-4471-6791-4
- Softcover ISBN
- 978-1-4471-7392-2
- Series ISSN
- 1610-3947
- Edition Number
- 1
- Number of Pages
- XXIV, 647
- Number of Illustrations
- 54 b/w illustrations
- Topics
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