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Vector dissimilarity and clustering
1Research Branch, Agriculture Canada, Ottawa, Ontario.
Mathematical Biosciences
|April 1, 1991
Abstract:
Based on the description of objects by m attributes, an m-element vector dissimilarity function is defined that, unlike scalar functions, retains the distinction among attributes. This function, which satisfies the conditions for a metric, allows the definition of betweenness, which can then be used for clustering. Applications to the subset-generation phase of conditional clustering and to nearest-neighbor-type algorithms are described.