Geodesic
Detecting a data set structure through the use of nonlinear projections search and optimization
Kybernetika, Tome 34 (1998) no. 4, p. [375].

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Detecting a cluster structure is considered. This means solving either the problem of discovering a natural decomposition of data points into groups (clusters) or the problem of detecting clouds of data points of a specific form. In this paper both these problems are considered. To discover a cluster structure of a specific arrangement or a cloud of data of a specific form a class of nonlinear projections is introduced. Fitness functions that estimate to what extent a given subset of data points (in the form of the corresponding projection) represents a good solution for the first or the second problem are presented. To find a good solution one uses a search and optimization procedure in the form of Evolutionary Programming. The problems of cluster validity and robustness of algorithms are considered. Examples of applications are discussed.
Classification : 62H30, 68T10
Keywords: cluster structure; nonlinear projection 
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     author = {Brailovsky, Victor L. and Har-Even, Michael},
     title = {Detecting a data set structure through the use of nonlinear projections search and optimization},
     journal = {Kybernetika},
     pages = {[375]},
     publisher = {mathdoc},
     volume = {34},
     number = {4},
     year = {1998},
     zbl = {1274.68376},
     language = {en},
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Brailovsky, Victor L.; Har-Even, Michael. Detecting a data set structure through the use of nonlinear projections search and optimization. Kybernetika, Tome 34 (1998) no. 4, p. [375]. http://geodesic.mathdoc.fr/item/KYB_1998__34_4_a3/