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Function-Point Cluster Analysis

Jeffrey Owen Katz and F. James Rohlf
Systematic Zoology
Vol. 22, No. 3 (Sep., 1973), pp. 295-301
DOI: 10.2307/2412309
Stable URL: http://www.jstor.org/stable/2412309
Page Count: 7
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Function-Point Cluster Analysis
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Abstract

The gradient clustering method of Ihm (1965) was reinvestigated and applied to several sets of real and artificial data. It is based on the technique of defining a function which has the property of being maximal in regions where there are high densities of points and low elsewhere. Points are considered to be in the same cluster if they are "under" the same local maximum of this function. The clusters obtained at different hierarchic levels are not necessarily nested. A generalization of the skyline graph is presented to depict such a system of cluster

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