The experimental comparisons show that this algorithm outperforms traditional KPCA and K-Nearest Neighbor classifier on both feature extraction and classification.

通过实验比对可知该算法效果在特征提取和分类方面均优于传统核主成分分析法以及最近邻分类器。

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Among, the classifier is designed by the nearest neighbor algorithm and trained based on the pulmonary nodules in LIDC as the sample data.

采用最近邻法设计分类器，并以LIDC库中的结节数据作为样本集，使用留一法进行分类器训练。

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In the paper, we use nearest neighbor classifier to carry the experiment through the ORL person face database.

本文实验选用最近邻分类器，并利用OR L人脸数据库进行对比实验。

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