A Comparison Study: Clustering using Self-Organizing Map and K-means Algorithm
Abstract: Nowadays clustering
is applied in many different scopes of study. There are many methods that have
been proposed, but the most widely used is K-means algorithm. Neural network
has been also usedin clustering case, and the most popular neural network
method for clustering is Self-Organizing Map (SOM). Both methods recently
become the most popular and powerful one. Many scholarstry to employ and
compare the performance of both mehods. Many papers have been proposed to
reveal which one is outperform the other. However, until now there is no exact
solution. Different scholar gives different conclusion. In this study, SOM and
K-means are compared using three popular data set. Percent misclassified and
output visualization graphs (separately and simultaneously with PCA) are
presented to verify the comparison result.
Penulis: Annisa Uswatun
Khasanah
Kode Jurnal: jptindustridd160433
