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- W2386539827 abstract "The k-Nearest-Neighbor (KNN) algorithm has been widely used in data mining areas. But, When the samples become more and more large and characteristic attributes become more and more numerous, then KNN algorithm becomes much lower. A improved KNN algorithm PRMKNN is proposed in the paper ,which first applies Principle Component Analysis(PCA)and rough set theory(RS) to realize feature extraction, We use PCA on selecting the input vector,and use RS on reducing the inessential factors for classification ,then simulation annealing algorithm is used to generate random subset of attributes, and with the simple voting method, the outputs of the multiple KNN classifiers are combined. The method can improve the classification precision and efficiency effectively." @default.
- W2386539827 created "2016-06-24" @default.
- W2386539827 creator A5015477789 @default.
- W2386539827 date "2010-01-01" @default.
- W2386539827 modified "2023-09-28" @default.
- W2386539827 title "A New Method to Scale Up Effect of K-Nearest-Neighbor" @default.
- W2386539827 hasPublicationYear "2010" @default.
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