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Non-uniqueness of numerical taxonomic structures
Luleå tekniska universitet.
Luleå tekniska universitet.
1993 (English)In: Binary Computing in Microbiology, ISSN 0266-304X, Vol. 5, no 4, p. 138-144Article in journal (Refereed) Published
Abstract [en]

The most important methods of numerical taxonomy in microbiology are based on so called reference matrices giving the frequencies of positive binary features of the different taxa. Microbiologists seem to have been tacitly assuming that every well-defined classification method, that is, every algorithm for constructing a reference matrix from data, leads to a unique classification (reference matrix). We use a mathematical result-that a finite mixture of multivariate Bernoulli distributions is always unidentifiable-to disprove this assumption. We show that the same classification method applied to the same data can always lead to different classifications. This result is of importance for the foundations of computational microbial taxonomy. It is illustrated by simple examples from the two main methods of classification and identification: the one where classification is performed first and then followed by identification, and cumulative classification where classification and identification are carried out simultaneously. The consequences of the non-uniqueness result for microbiological practice are discussed

Place, publisher, year, edition, pages
1993. Vol. 5, no 4, p. 138-144
National Category
Mathematical Analysis
Research subject
Mathematics
Identifiers
URN: urn:nbn:se:ltu:diva-7352Local ID: 5bab2480-0277-11de-a8bd-000ea68e967bOAI: oai:DiVA.org:ltu-7352DiVA, id: diva2:980241
Note
Godkänd; 1993; 20090224 (andbra)Available from: 2016-09-29 Created: 2016-09-29Bibliographically approved

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