Abstract:Clustering analysis (CA) techniques consist in, given a set of objects, estimating dense regions of points separated by sparse regions, according to the dimensions that describe these objects. Independently from the data nature – structured or non-structured -, we look for homogenous clouds of points, that define clusters, from which we want to extract some meaning. In other words, when doing CA, the analyst is searching for underlying structures in a multidimensional space for what one could assign some meani… Show more
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