Fitness functions in editing k-NN reference set by genetic algorithms
نویسنده
چکیده
-In a previous paper the use of GAs as an editing technique for the k-nearest neighbor (k-NN) classification technique has been suggested. Here we are looking at different fitness functions. An experimental study with the IRIS data set and with a medical data set has been carried out. Best results (smallest subsets with highest test classification accuracy) have been obtained by including in the fitness function a penalizing term accounting tbr the cardinality of the reference set. (C 1997 Pattern Recognition Society. Published by Elsevier Science Ltd. k-Nearest Neighbors (k-NN) rule Genetic algorithms Fitness functions Editing strategies
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ورودعنوان ژورنال:
- Pattern Recognition
دوره 30 شماره
صفحات -
تاریخ انتشار 1997