Data Mining Algorithms, Fog Computing

A cluster is a subset of targets which are “similar”. A subset of objects such that the length between any two targets in the cluster is less than the space between any object in the cluster and any object not located inside it. A connected region of multidimensional space containing the relatively high density of target. Clustering is a process of partitioning a set of data (or objects) into a lot of meaningful sub-divisions, called clusters. Help users understand the natural grouping or structure in a data set. Clustering is unsupervised classification and it has no predefined categories. Unsupervised classification is where the outcomes (groupings of pixels with common characteristics) are based on the software analysis of an image without the user providing sample classes. The information processing system uses techniques to see which pixels are related and groups them into categories. Used either as a stand-alone tool to bring insight into data distribution or as a preprocessing step for other algorithms (Shridhar D et al (2014). Data Mining Algorithms, Fog Computing

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