Recent advances in automatic classification

P. Michaud

Applied Stochastic Models and Data Analysis, 1991, vol. 7, issue 2, 167-182

Abstract: Traditional classification methods are divided into two broad types: hierarchical methods and non‐hierarchical methods in which the number of classes has to be fixed in advance. Both methods can handle both quantitative and qualitative data. A third type finds a partition optimizing a linear classification criterion (e.g. the Condorcet criterion) in which the number of classes does not have to be fixed in advance, but the data must be qualitative. A recent generalization, the ‘S theory’ can handle simultaneously both quantitative and qualitative data, and both linear and non‐linear classification criteria (in the space of paired comparisons of elements). With this ‘S theory’ the partition is obtained in order n (in terms of memory space and elementary operations), n being the number of elements to classify.

Date: 1991
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1002/asm.3150070206

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:apsmda:v:7:y:1991:i:2:p:167-182

Access Statistics for this article

More articles in Applied Stochastic Models and Data Analysis from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().