Foundations And Methods In Combinatorial And Statistical Data Analysis And Clustering

Download Foundations And Methods In Combinatorial And Statistical Data Analysis And Clustering full books in PDF, epub, and Kindle. Read online free Foundations And Methods In Combinatorial And Statistical Data Analysis And Clustering ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering

Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering
Author :
Publisher : Springer
Total Pages : 664
Release :
ISBN-10 : 9781447167938
ISBN-13 : 1447167937
Rating : 4/5 (937 Downloads)

Book Synopsis Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering by : Israël César Lerman

Download or read book Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering written by Israël César Lerman and published by Springer. This book was released on 2016-03-24 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering Related Books

Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering
Language: en
Pages: 664
Authors: Israël César Lerman
Categories: Computers
Type: BOOK - Published: 2016-03-24 - Publisher: Springer

DOWNLOAD EBOOK

This book offers an original and broad exploration of the fundamental methods in Clustering and Combinatorial Data Analysis, presenting new formulations and ide
Seriation in Combinatorial and Statistical Data Analysis
Language: en
Pages: 287
Authors: Israël César Lerman
Categories: Computers
Type: BOOK - Published: 2022-03-04 - Publisher: Springer Nature

DOWNLOAD EBOOK

This monograph offers an original broad and very diverse exploration of the seriation domain in data analysis, together with building a specific relation to clu
Data Clustering
Language: en
Pages: 648
Authors: Charu C. Aggarwal
Categories: Business & Economics
Type: BOOK - Published: 2013-08-21 - Publisher: CRC Press

DOWNLOAD EBOOK

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing
Foundations of Data Science
Language: en
Pages: 433
Authors: Avrim Blum
Categories: Computers
Type: BOOK - Published: 2020-01-23 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and a
Classification and Data Science in the Digital Age
Language: en
Pages: 393
Authors: Paula Brito
Categories: Computers
Type: BOOK - Published: 2023-12-07 - Publisher: Springer Nature

DOWNLOAD EBOOK

The contributions gathered in this open access book focus on modern methods for data science and classification and present a series of real-world applications.