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Analiza pohitritve algoritma gručenja DBSCAN z lokalno-občutljivim zgoščevanjem [Elektronski vir]Lukač, Niko ...In this paper an analysis of the improved DBSCAN (Density-based spatial clustering of applications with noise) algorithm is performed using Locality-sensitive hashing based on random geometric ... projections. The paper firstly provides theoretical background of DBSCAN and DBSCAN-LSH algorithms. Then results of the experiments follow by using well known clustering benchmark datasets from UCI repository in various size and number of dimensions, where performance of DBSCANLSH is evaulated in terms of accuracy using well established clustering algorithms’ evaluation indices. Lastly, the achieved computational speedup of using DBSCANLSH is evaluated.Type of material - conference contribution ; adult, seriousPublish date - 2023Language - slovenianCOBISS.SI-ID - 167309827
Author
Lukač, Niko |
Žalik, Borut |
Mongus, Domen |
Kavran, Domen |
Jesenko, David |
Kohek, Štefan, 1988-
Topics
algoritmi gručenja |
gručenje podatkov |
občutljivostne analize
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JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
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DRS, in which the journal is indexed
Database name | Field | Year |
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Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
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Lukač, Niko | 33709 |
Žalik, Borut | 06671 |
Mongus, Domen | 29243 |
Kavran, Domen | 52071 |
Jesenko, David | 37447 |
Kohek, Štefan, 1988- | 37222 |
Source: Personal bibliographies
and: SICRIS
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