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Far beyond the classical data models: symbolic data analysis
Author(s) -
NoirhommeFraiture Monique,
Brito Paula
Publication year - 2011
Publication title -
statistical analysis and data mining: the asa data science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.381
H-Index - 33
eISSN - 1932-1872
pISSN - 1932-1864
DOI - 10.1002/sam.10112
Subject(s) - computer science , symbolic data analysis , data mining , field (mathematics) , multivariate statistics , theoretical computer science , algorithm , mathematics , machine learning , pure mathematics
This paper introduces symbolic data analysis, explaining how it extends the classical data models to take into account more complete and complex information. Several examples motivate the approach, before the modeling of variables assuming new types of realizations are formally presented. Some methods for the (multivariate) analysis of symbolic data are presented and discussed. This is however far from being exhaustive, given the present dynamic development of this new field of research. © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 157–170, 2011