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Necessary Conditions for the Confidence Level of the Randomized Algorithm of Finding the True Number of Clusters. / Granichin, Oleg; Morozkov, Mikhail; Volkovich, Zeev.

2011 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL (ISIC). IEEE Canada, 2011. стр. 1002-1007 (IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL - PROCEEDINGS).

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › Рецензирование

Harvard

Granichin, O, Morozkov, M & Volkovich, Z 2011, Necessary Conditions for the Confidence Level of the Randomized Algorithm of Finding the True Number of Clusters. в 2011 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL (ISIC). IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL - PROCEEDINGS, IEEE Canada, стр. 1002-1007, IEEE International Symposium on Intelligent Control (ISIC)/IEEE Multi-Conference on Systems and Control (MSC), Denver, Колумбия, 28/09/11. https://doi.org/10.1109/ISIC.2011.6045413

APA

Granichin, O., Morozkov, M., & Volkovich, Z. (2011). Necessary Conditions for the Confidence Level of the Randomized Algorithm of Finding the True Number of Clusters. в 2011 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL (ISIC) (стр. 1002-1007). (IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL - PROCEEDINGS). IEEE Canada. https://doi.org/10.1109/ISIC.2011.6045413

Vancouver

Granichin O, Morozkov M, Volkovich Z. Necessary Conditions for the Confidence Level of the Randomized Algorithm of Finding the True Number of Clusters. в 2011 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL (ISIC). IEEE Canada. 2011. стр. 1002-1007. (IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL - PROCEEDINGS). https://doi.org/10.1109/ISIC.2011.6045413

Author

Granichin, Oleg ; Morozkov, Mikhail ; Volkovich, Zeev. / Necessary Conditions for the Confidence Level of the Randomized Algorithm of Finding the True Number of Clusters. 2011 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL (ISIC). IEEE Canada, 2011. стр. 1002-1007 (IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL - PROCEEDINGS).

BibTeX

@inproceedings{d504470e4e604eadb27d99c1108b9f0c,
title = "Necessary Conditions for the Confidence Level of the Randomized Algorithm of Finding the True Number of Clusters",
abstract = "One of the most difficult problems in cluster analysis is the identification of the number of groups in a given data set. In this paper we offer the approach in the framework of the common {"}elbow{"} methodology such that the true number of clusters is recognized as the slope discontinuity of the index function. A randomized algorithm has been suggested to allocate this position. The scenario approach is used to significantly reduce the computational complexity. We present weaker necessary conditions to provide a priori chosen level of confidence. In addition, we present a number of simulation examples of unknown huge number of groups clustering to demonstrate theoretical results. Finally, we note that necessary conditions can be relaxed more and ideas considered potentially can be extended to a wide range of real-time decision-making problems in control systems.",
keywords = "VALIDATION",
author = "Oleg Granichin and Mikhail Morozkov and Zeev Volkovich",
year = "2011",
doi = "10.1109/ISIC.2011.6045413",
language = "Английский",
series = "IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL - PROCEEDINGS",
publisher = "IEEE Canada",
pages = "1002--1007",
booktitle = "2011 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL (ISIC)",
address = "Канада",
note = "null ; Conference date: 28-09-2011 Through 30-09-2011",

}

RIS

TY - GEN

T1 - Necessary Conditions for the Confidence Level of the Randomized Algorithm of Finding the True Number of Clusters

AU - Granichin, Oleg

AU - Morozkov, Mikhail

AU - Volkovich, Zeev

PY - 2011

Y1 - 2011

N2 - One of the most difficult problems in cluster analysis is the identification of the number of groups in a given data set. In this paper we offer the approach in the framework of the common "elbow" methodology such that the true number of clusters is recognized as the slope discontinuity of the index function. A randomized algorithm has been suggested to allocate this position. The scenario approach is used to significantly reduce the computational complexity. We present weaker necessary conditions to provide a priori chosen level of confidence. In addition, we present a number of simulation examples of unknown huge number of groups clustering to demonstrate theoretical results. Finally, we note that necessary conditions can be relaxed more and ideas considered potentially can be extended to a wide range of real-time decision-making problems in control systems.

AB - One of the most difficult problems in cluster analysis is the identification of the number of groups in a given data set. In this paper we offer the approach in the framework of the common "elbow" methodology such that the true number of clusters is recognized as the slope discontinuity of the index function. A randomized algorithm has been suggested to allocate this position. The scenario approach is used to significantly reduce the computational complexity. We present weaker necessary conditions to provide a priori chosen level of confidence. In addition, we present a number of simulation examples of unknown huge number of groups clustering to demonstrate theoretical results. Finally, we note that necessary conditions can be relaxed more and ideas considered potentially can be extended to a wide range of real-time decision-making problems in control systems.

KW - VALIDATION

U2 - 10.1109/ISIC.2011.6045413

DO - 10.1109/ISIC.2011.6045413

M3 - статья в сборнике материалов конференции

T3 - IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL - PROCEEDINGS

SP - 1002

EP - 1007

BT - 2011 IEEE INTERNATIONAL SYMPOSIUM ON INTELLIGENT CONTROL (ISIC)

PB - IEEE Canada

Y2 - 28 September 2011 through 30 September 2011

ER -

ID: 60694658