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A framework for benchmarking clustering algorithms

Version 2 2024-06-19, 16:37

Version 1 2023-02-14, 03:44

journal contribution

posted on 2024-06-19, 16:37 authored by M Gagolewski

A framework for benchmarking clustering algorithms

History

Journal

SoftwareX

Volume

20

Article number

ARTN 101270

Publisher DOI

https://doi.org/10.1016/j.softx.2022.101270

ISSN

2352-7110

eISSN

2352-7110

Language

English

Author URL

https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000903860400007&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=a045e4b2bb1f2b747c68c720ec8913b7

Publication classification

C1 Refereed article in a scholarly journal

Publisher

ELSEVIER

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Categories

Software engineering not elsewhere classified

Keywords

Science & Technology Technology Computer Science, Software Engineering Computer Science Clustering Machine learning Benchmark data Noise points External cluster validity Partition similarity score

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All Rights Reserved

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