Hayashi / Yajima / Bock Data Science, Classification, and Related Methods

Proceedings of the Fifth Conference of the International Federation of Classification Societies (IFCS-96), Kobe, Japan, March 27–30, 1996
Erscheinungsjahr 2013
ISBN: 978-4-431-65950-1
Verlag: Springer Tokyo
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 780 Seiten, eBook

Reihe: Studies in Classification, Data Analysis, and Knowledge Organization

This volume, Data Science, Classification, and Related Methods, contains a selection of papers presented at the Fifth Conference of the International Federation of Oassification Societies (IFCS-96), which was held in Kobe, Japan, from March 27 to 30,1996. The volume covers a wide range of topics and perspectives in the growing field of data science, including theoretical and methodological advances in domains relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge discovery and seeking. It gives a broad view of the state of the art and is intended for those in the scientific community who either develop new data analysis methods or gather data and use search tools for analyzing and interpreting large and complex data sets. Presenting a wide field of applications, this book is of interest not only to data analysts, mathematicians, and statisticians but also to scientists from many areas and disciplines concerned with complex data: medicine, biology, space science, geoscience, environmental science, infonnation science, image and pattern analysis, economics, statistics, social sciences, psychology, cognitive science, behavioral science, marketing and survey research, data mining, and knowledge organization.

Zielgruppe

Research

Autoren/Hrsg.

Hayashi, Chikio

Yajima, Keiji

Bock, Hans H.

Ohsumi, Noboru

Tanaka, Yutaka

Baba, Yasumasa

Inhaltsverzeichnis

General Aspects of Data Science.- Methodologies in Classification.- Classification and Discrimination.- Related Approaches for Classification.- Correspondence Analysis, Quantification Methods, and Multidimensional Scaling.- Multivariate and Multidimensional Data Analysis.- Case Studies of Data Science.