The recognition is achieved by nearest neighbor algorithm.
用最近邻法进行分类和识别。
The paper studies the methods of feature selection in pattern recognition, and USES nearest neighbor classification accuracy as the evaluation criteria for feature selection.
研究了模式识别中的特征选择方法，采用最近邻分类正确率作为特征选择的性能评价函数。
The second step (recognition) is achieved by using a holographic nearest-neighbor algorithm (HNN), in which vectors obtained in the preprocessing step are used as inputs to it .
第二步，识别阶段，采用了一种亲笔最近相邻算法（HNN）。首先自学习预处理得到的数据，并得到对象的总的特征。再通过HNN算法来识别对象。
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