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Cordeiro de Amorim, Renato, Shestakov, Andrei, Mirkin, Boris, Makarenkov, Vladimir (2017) The Minkowski central partition as a pointer to a suitable distance exponent and consensus partitioning. Pattern Recognition, 67. 62-72 doi:10.1016/j.patcog.2017.02.001

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Reference TypeJournal (article/letter/editorial)
TitleThe Minkowski central partition as a pointer to a suitable distance exponent and consensus partitioning
JournalPattern Recognition
AuthorsCordeiro de Amorim, RenatoAuthor
Shestakov, AndreiAuthor
Mirkin, BorisAuthor
Makarenkov, VladimirAuthor
Year2017 (July)Volume67
PublisherElsevier BV
DOIdoi:10.1016/j.patcog.2017.02.001Search in ResearchGate
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Mindat Ref. ID9366946Long-form Identifiermindat:1:5:9366946:5
GUID0
Full ReferenceCordeiro de Amorim, Renato, Shestakov, Andrei, Mirkin, Boris, Makarenkov, Vladimir (2017) The Minkowski central partition as a pointer to a suitable distance exponent and consensus partitioning. Pattern Recognition, 67. 62-72 doi:10.1016/j.patcog.2017.02.001
Plain TextCordeiro de Amorim, Renato, Shestakov, Andrei, Mirkin, Boris, Makarenkov, Vladimir (2017) The Minkowski central partition as a pointer to a suitable distance exponent and consensus partitioning. Pattern Recognition, 67. 62-72 doi:10.1016/j.patcog.2017.02.001
In(2017) Pattern Recognition Vol. 67. Elsevier BV

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Cordeiro de Amorim, Renato, Mirkin, Boris (2012) Minkowski metric, feature weighting and anomalous cluster initializing in K-Means clustering. Pattern Recognition, 45 (3). 1061-1075 doi:10.1016/j.patcog.2011.08.012
Cordeiro de Amorim, Renato, Makarenkov, Vladimir, Mirkin, Boris (2016) A-Ward pβ : Effective hierarchical clustering using the Minkowski metric and a fast k -means initialisation. Information Sciences, 370. 343-354 doi:10.1016/j.ins.2016.07.076
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Jain, Brijnesh J. (2017) Consistency of mean partitions in consensus clustering. Pattern Recognition, 71. 26-35 doi:10.1016/j.patcog.2017.04.021
Panday, Deepak, Cordeiro de Amorim, Renato, Lane, Peter (2018) Feature weighting as a tool for unsupervised feature selection. Information Processing Letters, 129. 44-52 doi:10.1016/j.ipl.2017.09.005
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