Finding prototypes for nearest neighbour classification by means of gradient descent and deterministic annealing
نویسنده
چکیده
Abstraet--A new method is presented to find prototypes for a nearest neighbour classifier. The prototype locations are opfimised through a gradient descent and a deterministic annealing process. The proposed algorithm also includes an initialisation strategy which alms to provide the maximum classification rate on the training set with the minimum number of prototypes. Experiments show the efficiency of this algorithm on both real and artificial data. Copyright © 1997 Pattern Recognition Society. Published by Elsevier Science Ltd.
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عنوان ژورنال:
- Pattern Recognition
دوره 30 شماره
صفحات -
تاریخ انتشار 1997