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pro vyhledávání: '"Shaoyi Liang"'
Autor:
Shaoyi Liang, Deqiang Han
Publikováno v:
Sensors, Vol 17, Iss 10, p 2226 (2017)
Closeness measures are crucial to clustering methods. In most traditional clustering methods, the closeness between data points or clusters is measured by the geometric distance alone. These metrics quantify the closeness only based on the concerned
Externí odkaz:
https://doaj.org/article/1b6db32f16e544e286baf2a03e86460a
Publikováno v:
Applied Soft Computing. 95:106583
Different clustering algorithms with different parameter settings can produce various partitions on the input data. Without the priori knowledge, it is difficult for users to select the proper clustering algorithm and the parameters for the specific
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b6a4c554ec9dfbc9256872afe35a31c
https://doi.org/10.1016/j.asoc.2020.106583
https://doi.org/10.1016/j.asoc.2020.106583
Autor:
Shaoyi Liang, Deqiang Han
Publikováno v:
2018 Chinese Automation Congress (CAC).
One major difficulty in clustering is to discover the underlying structure of the input data space under complex situations without much prior information. This problem consists of two aspects, i.e., to determine the target clusters number based on t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7c7d8814b44ea8258c9940ed9f8c2f38
https://doi.org/10.1109/cac.2018.8623532
https://doi.org/10.1109/cac.2018.8623532
Autor:
Shaoyi Liang, Deqiang Han
Publikováno v:
FUSION
Topics on clustering ensemble have attracted much attention in recent years. In many clustering ensemble frameworks, the simple partitional clustering methods, e.g., the most famous κ-means, are used as the ensemble's member “clusterers”, due to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c9a72a4197bc9a36cb55619e7437458
https://doi.org/10.23919/icif.2017.8009784
https://doi.org/10.23919/icif.2017.8009784
Publikováno v:
IJCNN
Closeness measures are crucial to clustering methods. In most traditional clustering methods, the closeness between data points or clusters is measured by the geometric distances alone. These metrics quantify the closeness only based on the concerned
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4912fc3365718f315178763a5be397db
https://doi.org/10.1109/ijcnn.2017.7965961
https://doi.org/10.1109/ijcnn.2017.7965961
Publikováno v:
IET International Conference on Information Science and Control Engineering 2012 (ICISCE 2012).
In the complicated pattern recognition, multiple classifier systems (MCSs) can usually obtain higher classification accuracy compared to a single classifier when there is high diversity among member classifiers. Therefore, diversity measures are espe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fc6b90f059f2e8d8d9fb43038b2ad575
https://doi.org/10.1049/cp.2012.2350
https://doi.org/10.1049/cp.2012.2350
Autor:
Shaoyi Liang, Zhiqiang Wang
Publikováno v:
4th International Power Electronics & Motion Control Conference, 2004. IPEMC 2004; 2004, p908-908, 1p