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Seriation in Combinatorial and Statistical Data Analysis
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Seriation in Combinatorial and Statistical Data Analysis

2022 ed.

Book Details

Format Paperback / Softback
ISBN-10 3030926966
ISBN-13 9783030926960
Edition 2022 ed.
Publisher Springer Nature Switzerland AG
Imprint Springer Nature Switzerland AG
Country of Manufacture GB
Country of Publication GB
Publication Date Mar 6th, 2023
Print length 277 Pages
Weight 436 grams
Dimensions 15.70 x 23.50 x 1.80 cms
Ksh 25,200.00
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This monograph offers an original broad and very diverse exploration of the seriation domain in data analysis, together with building a specific relation to clustering.Relative to a data table crossing a set of objects and a set of descriptive attributes, the search for orders which correspond respectively to these two sets is formalized mathematically and statistically. State-of-the-art methods are created and compared with classical methods and a thorough understanding of the mutual relationships between these methods is clearly expressed. The authors distinguish two families of methods:Geometric representation methodsAlgorithmic and Combinatorial methodsOriginal and accurate methods are provided in the framework for both families. Their basis and comparison is made on both theoretical and experimental levels. The experimental analysis is very varied and very comprehensive. Seriation in Combinatorial and Statistical Data Analysis has a unique character in the literature falling within the fields of Data Analysis, Data Mining and Knowledge Discovery. It will be a valuable resource for students and researchers in the latter fields.
This monograph offers an original broad and very diverse exploration of the seriation domain in data analysis, together with building a specific relation to clustering.

Relative to a data table crossing a set of objects and a set of descriptive attributes, the search for orders which correspond respectively to these two sets is formalized mathematically and statistically.

State-of-the-art methods are created and compared with classical methods and a thorough understanding of the mutual relationships between these methods is clearly expressed. The authors distinguish two families of methods:

  • Geometric representation methods
  • Algorithmic and Combinatorial methods

Original and accurate methods are provided in the framework for both families. Their basis and comparison is made on both theoretical and experimental levels. The experimental analysis is very varied and very comprehensive. Seriation in Combinatorial and Statistical Data Analysis has a unique character in the literature falling within the fields of Data Analysis, Data Mining and Knowledge Discovery. It will be a valuable resource for students and researchers in the latter fields.


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