A Nonparametric Valley-Seeking Technique for Cluster Analysis
Proceedings of the Second International Joint Conference on Artificial Intelligence. Pages 411-416.
Abstract
The probl .. of clustering .ultivsriate observation• il viewed a1 the replacement of a 1et of vector• with a 1et of label• and repre1entative vector•. A general criterion for clu1tering i1 derived as · a mea1ure of repre1entation error. Some 1pecial ease• are derived by 1iaplifying the general criterion. A general algorithm for finding the optimum cla11ification with reapeet to a given criterion 11 de_rived. For a p1rtieular ease, the algorithm reduces to a repeated application of a 1traightforward deei1ion rule which behave• as a valley-leeking technique. A1ymptotic propertiel of the procedure are developed. Numerical examples are pre1ented for the finite uaple case.
@inproceedings{ijcai1971p42,
title = {A Nonparametric Valley-Seeking Technique for Cluster Analysis},
author = {Koontz, Warren L. G. and Fukunaga, Keinosuke},
booktitle = {Proceedings of the Second International Joint Conference on
Artificial Intelligence, {IJCAI-71}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {D.C. Cooper},
pages = {411--416},
year = {1971},
url = {https://ijcai.org/proceedings/1971/42},
}
TY - CPAPER TI - A Nonparametric Valley-Seeking Technique for Cluster Analysis AU - Koontz, Warren L. G. AU - Fukunaga, Keinosuke T2 - Proceedings of the Second International Joint Conference on Artificial Intelligence, IJCAI-71 PB - International Joint Conferences on Artificial Intelligence PY - 1971 SP - 411 EP - 416 UR - https://ijcai.org/proceedings/1971/42 ER -Copied
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