University of Sussex
Browse

File(s) not publicly available

Accuracy and robustness of clustering algorithms for small-size applications in bioinformatics

journal contribution
posted on 2023-06-08, 18:25 authored by Pamela Minicozzi, Fabio Rapallo, Enrico Scalas, Francesco Dondero
The performance (accuracy and robustness) of several clustering algorithms is studied for linearly dependent random variables in the presence of noise. It turns out that the error percentage quickly increases when the number of observations is less than the number of variables. This situation is common situation in experiments with DNA microarrays. Moreover, an 'a posteriori' criterion to choose between two discordant clustering algorithm is presented.

History

Publication status

  • Published

Journal

Physica A Statistical Mechanics and its Applications

ISSN

0378-4371

Publisher

Elsevier

Issue

25

Volume

387

Page range

6310-6318

Department affiliated with

  • Mathematics Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2014-09-26

Usage metrics

    University of Sussex (Publications)

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC