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A Note on the Effectiveness of the Least Squares Consensus Clustering
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Миркин Б. Г., Шестаков А. В.
ПУБЛИКАЦИЯ ПОДГОТОВЛЕНА ПО РЕЗУЛЬТАТАМ ПРОЕКТА:
В книге
Vol. 92. , Berlin : Springer, 2014
Миркин Б. Г., , in : Models, Algorithms, and Technologies for Network Analysis. Vol. 59.: NY : Springer, 2013. P. 101-126.
Добавлено: 22 ноября 2013 г.
Миркин Б. Г., Andrey Shestakov, , in : Clusters, orders, trees: methods and applications. In Honor of Boris Mirkin's 70th Birthday. Vol. 92.: Berlin : Springer, 2014.
We develop a consensus clustering framework proposed three decades ago in Russia and experimentally demonstrate that our least squares consensus clustering algorithm consistently outperforms several recent consensus clustering methods. ...
Добавлено: 4 ноября 2013 г.
Миркин Б. Г., , in : Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. Issue 8170: Lecture Notes in Artificial Intelligence.: Heidelberg : Springer, 2013. P. 26-37.
A least-squares data approximation approach to finding individual clusters is advocated. A simple local optimization algorithm leads to suboptimal clusters satisfying some natural tightness criteria. Three versions of an iterative extraction approach are considered, leading to a portrayal of the cluster structure of the data. Of these, probably most promising is what is referred to ...
Добавлено: 29 октября 2013 г.
Бочаров А. А., Гнатышак Д. В., Игнатов Д. И. и др., , in : CLA 2016: Proceedings of the Thirteenth International Conference on Concept Lattices and Their Applications. CEUR Workshop Proceedings. Vol. 1624.: M. : Higher School of Economics, National Research University, 2016. P. 45-56.
Добавлено: 24 октября 2016 г.
Миркин Б. Г., Nascimento S., Information Sciences 2012 No. 183 P. 16-34
An additive spectral method for fuzzy clustering is proposed. The method operates on a clustering model which is an extension of the spectral decomposition of a square matrix. The computation proceeds by extracting clusters one by one, which makes the spectral approach quite natural. The iterative extraction of clusters, also, allows us to draw several ...
Добавлено: 16 ноября 2012 г.
Миркин Б. Г., Шестаков А. В., , in : Advances in Information Retrieval. : L. : Springer, 2013. P. 764-768.
Произведена эксперементальная демонстранция превосходства алгоритмов консенсусной кластеризации, основанных на методе наименьших квадратов, по сравнению с недавними алгоритмами этой же области. ...
Добавлено: 15 апреля 2013 г.