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Method Of Key Vectors Extraction Using R-Cloud Classifiers



    (School of Nuclear Engineering, Purdue University, W. Lafayette, IN, 47907, USA)



    (Sun Microsystems, Inc. San Diego, CA, 92121, USA)



    (School of Nuclear Engineering, Purdue University, W. Lafayette, IN, 47907, USA)



    (Sun Microsystems, Inc., San Diego, CA, 92121, USA)

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    A novel method for reducing a training data set in the context of nonparametric classification is proposed. The new method is based on the method of R-clouds. The advantages of the R-cloud classification method introduced recently are being investigated. The separating boundary of the R-cloud classifier is represented using Rvachev functions. The method of key vectors extraction uses the value of the R-cloud function to quantify the disturbance of the separating boundary, which is caused by removal of one data vector from the design dataset. The R-cloud method was found instructive and practical in a number of engineering problems related to pattern classification.

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    Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal New Mathematics and Natural Computation.

    Volume (Year): 03 (2007)
    Issue (Month): 03 ()
    Pages: 419-426

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    Handle: RePEc:wsi:nmncxx:v:03:y:2007:i:03:p:419-426
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