A Genetic Algorithm for Learning Weights in A Similarity Function
نویسندگان
چکیده
One large problem when employing a similarity function to measure the similarities between new and prior cases is to determine the weights of the features. This paper proposes a new method of learning weights using a genetic algorithm based on the similarity information of given examples. This method is suitable for both linear and nonlinear similarity functions. Our experimental results show the computational e ciency of the proposed approach.
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تاریخ انتشار 1997