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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Zakiah Ahmad
Universiti Teknologi MARA
Computer Science & IT Engineering

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Review of single clustering methods Nurshazwani Muhamad Mahfuz; Marina Yusoff; Zakiah Ahmad
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 8, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (435.105 KB) | DOI: 10.11591/ijai.v8.i3.pp221-227

Abstract

Clustering provides a prime important role as an unsupervised learning method in data analytics to assist many real-world problems such as image segmentation, object recognition or information retrieval. It is often an issue of difficulty for traditional clustering technique due to non-optimal result exist because of the presence of outliers and noise data. This review paper provides a review of single clustering methods that were applied in various domains. The aim is to see the potential suitable applications and aspect of improvement of the methods. Three categories of single clustering methods were suggested, and it would be beneficial to the researcher to see the clustering aspects as well as to determine the requirement for clustering method for an employment based on the state of the art of the previous research findings.
Co-Authors Marina Yusoff Nurshazwani Muhamad Mahfuz