Zobrazeno 1 - 10
of 59
pro vyhledávání: '"adaptive Mahalanobis clustering"'
Autor:
Morales-Esteban, Antonio a, Martínez-Álvarez, Francisco b, Scitovski, Sanja c, Scitovski, Rudolf d, ⁎
Publikováno v:
In Computers and Geosciences December 2014 73:132-141
Publikováno v:
Croatian Operational Research Review, Vol 7, Iss 1, Pp 81-96 (2016)
The paper discusses the problem of grouping and ranking of research projects submitted for a call. The projects are grouped into clusters based on the assessment obtained in the review procedure and by using the adaptive Mahalanobis clustering method
Externí odkaz:
https://doaj.org/article/fdaaf43c51634ff78c675afffc9dccf1
Publikováno v:
Croatian Operational Research Review
Volume 7
Issue 1
Croatian Operational Research Review, Vol 7, Iss 1, Pp 81-96 (2016)
Volume 7
Issue 1
Croatian Operational Research Review, Vol 7, Iss 1, Pp 81-96 (2016)
The paper discusses the problem of grouping and ranking of research projects submitted for a call. The projects are grouped into clusters based on the assessment obtained in the review procedure and by using the adaptive Mahalanobis clustering method
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9279a9f6a6faf75845babc0978351477
https://www.bib.irb.hr/811202
https://www.bib.irb.hr/811202
In this paper we construct an efficient adaptive Mahalanobis k-means algorithm. In addition, we propose a new efficient algorithm to search for a globally optimal partition obtained by using the adoptive Mahalanobis distance-like function. The algori
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a16864e96ab77e61decf76a15cdcf773
https://doi.org/10.1016/j.cageo.2014.09.003
https://doi.org/10.1016/j.cageo.2014.09.003
Autor:
Morales-Esteban, Antonio a, Martínez-Álvarez, Francisco b, Scitovski, Sanja c, Scitovski, Rudolf d, e, ⁎
Publikováno v:
In Computers and Geosciences November 2021 156
Publikováno v:
In Pattern Recognition December 2016 60:824-834
Autor:
Sanja Scitovski, Nataša Šarlija
Publikováno v:
Croatian Operational Research Review, Vol 5, Iss 2, Pp 235-245 (2014)
The aim of this paper is to segment retail clients by using adaptive Mahalanobis clustering in a way that each segment can be suitable for separate credit scoring development such that a better risk assessment of retail clients could be accomplished.
Externí odkaz:
https://doaj.org/article/a7c18e9488cf4898a8429b347ca87665
Publikováno v:
Croatian Operational Research Review; 2016, Vol. 7 Issue 1, p81-96, 16p
Autor:
Sharma, Ashish1 (AUTHOR) 2018rec9054@mnit.ac.in, Vijay, Rahul Kumar2 (AUTHOR), Nanda, Satyasai Jagannath1 (AUTHOR)
Publikováno v:
Neural Computing & Applications. Apr2023, Vol. 35 Issue 11, p8081-8108. 28p.
Autor:
Liu, Chicheng1 (AUTHOR), Chen, Rui1 (AUTHOR), Chen, Ken1 (AUTHOR), Xu, Jing1 (AUTHOR) jingxu@tsinghua.edu.cn
Publikováno v:
Machine Vision & Applications. Jul2022, Vol. 33 Issue 4, p1-17. 17p.