A Modified Version of K-Means Algorithm
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F22%3A43896308" target="_blank" >RIV/44555601:13440/22:43896308 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1007/978-3-030-89899-1_32" target="_blank" >https://doi.org/10.1007/978-3-030-89899-1_32</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-89899-1_32" target="_blank" >10.1007/978-3-030-89899-1_32</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
A Modified Version of K-Means Algorithm
Popis výsledku v původním jazyce
In this work is presented a modified version of the K-Means which identifies cluster stability. The stability is defined by a threshold based on a percentage of the largest displacement of centroid at first iteration. A cluster is considered stable when the largest centroid displacement in the current iteration achieves the 10% of threshold, and objects that remains in the same cluster in two consecutive iterations are removed from the classification phase in subsequent iterations. Eight different instances were used to validate the proposal, three synthetics and five reals. The modified version was compared against the standard and three related work versions. Results shows that the proposal reduced the execution time up to 92.14% regarding the standard version with only a 3.73% in the quality reduction. Despite the new version do not has the major reduction time in all cases, the algorithm reaches the best values for quality of grouping.
Název v anglickém jazyce
A Modified Version of K-Means Algorithm
Popis výsledku anglicky
In this work is presented a modified version of the K-Means which identifies cluster stability. The stability is defined by a threshold based on a percentage of the largest displacement of centroid at first iteration. A cluster is considered stable when the largest centroid displacement in the current iteration achieves the 10% of threshold, and objects that remains in the same cluster in two consecutive iterations are removed from the classification phase in subsequent iterations. Eight different instances were used to validate the proposal, three synthetics and five reals. The modified version was compared against the standard and three related work versions. Results shows that the proposal reduced the execution time up to 92.14% regarding the standard version with only a 3.73% in the quality reduction. Despite the new version do not has the major reduction time in all cases, the algorithm reaches the best values for quality of grouping.
Klasifikace
Druh
D - Stať ve sborníku
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2022
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název statě ve sborníku
Lecture Notes in Networks and Systems
ISBN
—
ISSN
2367-3370
e-ISSN
2367-3389
Počet stran výsledku
11
Strana od-do
299-308
Název nakladatele
Springer Nature
Místo vydání
Cham
Místo konání akce
Fukuoka, Japan
Datum konání akce
28. 10. 2021
Typ akce podle státní příslušnosti
WRD - Celosvětová akce
Kód UT WoS článku
000722277600032