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K-means remains a widely used algorithm due to its efficiency, although its performance can suffer in high ... 19 These themes are prevalent in clinical and population studies.20 For example, risk ...

The funds in most U.S. retirement accounts are pretty basic - stocks and bonds. But what about investing in all kinds of other stuff? That's the idea behind a recent executive order signed by ...

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: The performance of k-means clustering algorithm depends on the selection of distance metrics. The Euclid distance is commonly chosen as the similarity measure in k-means clustering algorithm ...