Comparison of Nearest Neighbor Condensing Methods.
Recently, support vector machine (SVM) has become one of the most efficient methods for pattern classifi cation due to its high accuracy and generalization capability. However, its main limitation is the ability to scale up for large data sets as the storage requirement increases with the number of training patterns leading to impractical training time. In this paper, various efficient condensing methods were com-pared to achieve this goal.
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