Jump to content

Symbolic data analysis

From Wikipedia, the free encyclopedia
This is an old revision of this page, as edited by Qzxpqbp (talk | contribs) at 12:50, 3 June 2012 (Created page with ''''Symbolic data analysis''' ( or '''SDA''') is an extension of standard data analysis where symbolic data tables are used as input and symbolic objects are outp...'). The present address (URL) is a permanent link to this revision, which may differ significantly from the current revision.
(diff) ← Previous revision | Latest revision (diff) | Newer revision → (diff)

Symbolic data analysis ( or SDA) is an extension of standard data analysis where symbolic data tables are used as input and symbolic objects are outputted as a result. The data units are called symbolic since they are more complex than standard ones, as they not only contain a value or magnitude, but also include internal variation and structure. It is based on four spaces: the space of individuals, the space of concepts, the space of descriptions, and the space of symbolic objects. The space of descriptions models individuals, while the space of symbolic objects models concepts.[1]

References

  1. ^ Diday, Edwin; Esposito, Floriana (2003). "An introduction to symbolic data analysis and the SODAS software". Intelligent Data Analysis. 7 (6): 583–601. {{cite journal}}: Unknown parameter |month= ignored (help)