關鍵字查詢 | 類別:期刊論文 | | 關鍵字:Stray Example Sheltering by Loss Regularized SVM and k NN Preprocessor

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1 97/2 機電系 楊智旭 副教授 期刊論文 發佈 Stray Example Sheltering by Loss Regularized SVM and k NN Preprocessor , [97-2] :Stray Example Sheltering by Loss Regularized SVM and k NN Preprocessor期刊論文Stray Example Sheltering by Loss Regularized SVM and k NN PreprocessorYang, Chan-yun; Hsu, Che-chang; Yang, Jr-syu淡江大學機械與機電工程學系k-nearest-neighbor preprocessor; Stray training examples; Support vector machines; Classification; Pattern recognitionNew York: Springer New York LLCNeural Processing Letters 29(1), pp.7-27This paper presents a new model developed by merging a non-parametric k-nearest-neighbor (kNN) preprocessor into an underlying support vector machine (SVM) to provide shelters for meaningful training examples, especially for stray examples scattered around their counterpart examples with different class labels. Motivated by the method of adding heavier penalty to the stray example to attain a stricter loss function for optimization, the model acts to shelter stray examples. The model consists of a filtering kNN emphasizer stage and a classical classification stage. First, the filtering kNN emphasizer st
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