
Seriation in Combinatorial and Statistical Data Analysis
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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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Persons
Teacher-researcher in Applied Mathematics and Computer Science, Henri Leredde worked as a member of the Mathematics department at Sorbonne Paris Nord University. He was Director of Studies for the "Telecom and Networks" part of the Sup Galilée engineering school. He is now an associate researcher at LAGA (1) . In addition, he is an archaeologist, specialist in Gallo-Roman pottery and also practices numerous aerial surveys in archeology as a pilot.
(1) - LAGA : Laboratoire Analyse, Géométrie et Applications, CNRS UMR 7539 and Department of Mathematics, Institut Galilée, Sorbonne Paris-Nord University.
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