Abstract: This paper presents a new method that combines deep k-means clustering with granule mining approaches to utilise contextual information for improving outlier detection and classification.
Abstract: K-means clustering is a popular unsupervised machine learning method widely used in various applications, such as data mining, image processing, and social sciences. However, clustering can ...
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