Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering

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 provid...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Lerman, Israël César (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Springer London : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:Advanced Information and Knowledge Processing,
Temas:
Data mining.
Mathematical statistics-Data processing.
Discrete mathematics.
Data Mining and Knowledge Discovery.
Statistics and Computing.
Discrete Mathematics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Preface
  • On Some Facets of the Partition Set of a Finite Set
  • Two Methods of Non-hierarchical Clustering
  • Structure and Mathematical Representation of Data
  • Ordinal and Metrical Analysis of the Resemblance Notion
  • Comparing Attributes by a Probabilistic and Statistical Association I
  • Comparing Attributes by a Probabilistic and Statistical Association II
  • Comparing Objects or Categories Described by Attributes
  • The Notion of "Natural" Class, Tools for its Interpretation. The Classifiability Concept
  • Quality Measures in Clustering
  • Building a Classification Tree
  • Applying the LLA Method to Real Data
  • Conclusion and Thoughts for Future Works.

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