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The increasing demand for dealing with uncertainty in data has led to the development of effective and efficient approaches in the data management and mining contexts. Clustering uncertain data objects has particularly attracted great attention in the data mining community. Most existing clustering methods however have urgently to come up with a number of issues, some of which are related to a poor...
This article proposes a point of view (sub-space modelling), a post-processing strategy (relating to sub-optimal model) and a pre-processing strategy involving a novel cross-validation algorithm in machine learning with a focus on small datasets. To overcome the limitations imposed by small datasets, this approach leverages human expertise in being able to visualise or conceptualize clusters at high...
One of the most famous approaches for the segmentation of color images is finding clusters in the color space. Shapes of these clusters are often complex and the time complexity of the existing algorithms for finding clusters of different shapes is usually high. In this paper, a novel clustering algorithm is proposed and used for the image segmentation purpose. This algorithm distinguishes clusters...
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