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Article

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Title

Comparison of algorithms for clustering incomplete data

Authors

Year of publication

2014

Published in

Foundations of Computing and Decision Sciences

Journal year: 2014 | Journal volume: vol. 39 | Journal number: no. 2

Article type

scientific article

Publication language

english

Keywords
EN
  • clustering
  • incomplete data
  • missing value
  • marginalisation
  • imputation
  • IFCM
  • OCS
  • NPS
  • NCS
Abstract

EN The missing values are not uncommon in real data sets. The algorithms and methods used for the data analysis of complete data sets cannot always be applied to missing value data. In order to use the existing methods for complete data, the missing value data sets are preprocessed. The other solution to this problem is creation of new algorithms dedicated to missing value data sets. The objective of our research is to compare the preprocessing techniques and specialised algorithms and to find their most advantageous usage.

Pages (from - to)

107 - 127

DOI

10.2478/fcds-2014-0007

URL

https://sciendo.com/article/10.2478/fcds-2014-0007

License type

CC BY-NC-ND (attribution - noncommercial - no derivatives)

Full text of article

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Access level to full text

public

Ministry points / journal

15

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