20.500.12556/DKUM-89496 Implementacija k-means gručenja z genetskim algoritmom Implementing k-means clustering with a genetic algorithm K-means algoritem je eden najpopularnejših in najučinkovitejših algoritmov gručenja podatkov. Kljub temu algoritem predstavlja izziv, saj je občutljiv na začetno postavitev centroidov gruč. Zato lahko algoritem stremi k lokalnemu optimumu in ne h globalno optimalni rešitvi. Namen diplomskega dela je implementacija optimiziranega k-means algoritma, manj občutljivega na začetne centroide gruč, z uporabo genetskega algoritma. Delo se osredotoča na postopek gručenja in genetski algoritem. Implementacija je izvedena v programskem jeziku Python s knjižnico NiaPy. Na koncu so predstavljeni rezultati eksperimentov, kjer je izvedena primerjava standardnega in optimiziranega k-means algoritma na različnih podatkovnih množicah. The k-means algorithm is one of the most popular and effective clustering algorithms. However, it presents a challenge as it is sensitive to the initial placement of cluster centroids. Therefore, the algorithm can converge to a local optimum rather than a globally optimal solution. The purpose of this thesis is to implement an optimized k-means algorithm that is less sensitive to the initial cluster centroid using a genetic algorithm. The work focuses on the clustering process and the genetic algorithm. The implementation will be carried out in the Python programming language using the NiaPy library. Finally, the results of the experiments comparing the standard k-means and the optimized k-means algorithm on various datasets will be presented. gručenje k-means genetski algoritem centroidi clustering k-means genetic algorithm centroids true true false [A. Šaruga] Slovenski jezik Angleški jezik Diplomsko delo/naloga 2024-07-15 11:45:02 2024-09-19 15:32:26 2024-12-20 14:15:00 0000-00-00 00:00:00 2024 0 Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004.421.2:004.627(043.2) 220095747 VS_Saruga_Alen_2024.pdf VS_Saruga_Alen_2024.pdf 1 0058A7884EEA2DE0F2FAC15B8F04B6FA 3e151aa77c5ebc6e01bb590004c789767a821a7e5b6466fea25233fb26ed84cd 9e7d358a-4296-11ef-99b3-00155d000105 https://dk.um.si/Dokument.php?lang=slv&id=181480 Fakulteta za elektrotehniko, računalništvo in informatiko 0 0 0