Classification is the process of choosing the class of a new data point based on the known classifications of the observations in the database. The k Nearest Neighbor (k-NN) is a classification algorithm to choose the most frequent class among the k training samples nearest to the query point. We co...
#k-nearest neighbor;weighted k-nearest neighbor;alternative k-nearest neighbor;eigenvalue-based feature extraction;optimal choice of k;k-neighborhood components analysis;
|학위수여기관||Graduate School, Yonsei University|
|학과||Dept. of Computational Science and Engineering|
|키워드||k-nearest neighbor, weighted k-nearest neighbor, alternative k-nearest neighbor, eigenvalue-based feature extraction, optimal choice of k, k-neighborhood components analysis|
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