Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
1/2-Approximation polynomial-time algorithm for a problem of searching a subset. / Ageev, Alexander; Kel'Manov, Alexander; Pyatkin, Artem и др.
Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017. Institute of Electrical and Electronics Engineers Inc., 2017. стр. 8-12 8109827.Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
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TY - GEN
T1 - 1/2-Approximation polynomial-time algorithm for a problem of searching a subset
AU - Ageev, Alexander
AU - Kel'Manov, Alexander
AU - Pyatkin, Artem
AU - Khamidullin, Sergey
AU - Shenmaier, Vladimir
N1 - Publisher Copyright: © 2017 IEEE.
PY - 2017/11/14
Y1 - 2017/11/14
N2 - The work considers the mathematical aspects of one of the most fundamental problems of data analysis: search (choice) among a collection of objects for a subset of similar ones. In particular, the problem appears in connection with data editing and cleaning (removal of irrelevant (not similar) elements). We consider the model of this problem, i.e., the problem of searching for a subset of largest cardinality in a finite set of points of the Euclidean space for which quadratic variation of points with respect to its unknown centroid does not exceed a given fraction of the quadratic variation of points of the input set with respect to its centroid. It is proved that the problem is strongly NP-hard. A polynomial-time 1/2-approximation algorithm is proposed. The results of the numerical simulation demonstrating the effectiveness of the algorithm are presented.
AB - The work considers the mathematical aspects of one of the most fundamental problems of data analysis: search (choice) among a collection of objects for a subset of similar ones. In particular, the problem appears in connection with data editing and cleaning (removal of irrelevant (not similar) elements). We consider the model of this problem, i.e., the problem of searching for a subset of largest cardinality in a finite set of points of the Euclidean space for which quadratic variation of points with respect to its unknown centroid does not exceed a given fraction of the quadratic variation of points of the input set with respect to its centroid. It is proved that the problem is strongly NP-hard. A polynomial-time 1/2-approximation algorithm is proposed. The results of the numerical simulation demonstrating the effectiveness of the algorithm are presented.
KW - Approximation algorithm
KW - Computational complexity
KW - Data mining
KW - Machine learning
KW - Minimal sum of squared distances
KW - Optimization problems
KW - Subset with the largest cardinality
UR - http://www.scopus.com/inward/record.url?scp=85040528319&partnerID=8YFLogxK
U2 - 10.1109/SIBIRCON.2017.8109827
DO - 10.1109/SIBIRCON.2017.8109827
M3 - Conference contribution
AN - SCOPUS:85040528319
SP - 8
EP - 12
BT - Proceedings - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2017
Y2 - 18 September 2017 through 22 September 2017
ER -
ID: 9112512