A clustering-based and supervised intrusion detection method was proposed with new distance definition for mixed-attribute data and improved nearest neighbor classification method.

基于一种用于混合属性数据的距离定义和改进的最近邻分类方法，提出了一种基于聚类的有指导的入侵检测方法。

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Furthermore, combined with the nearest distance classifier, the support vector machine (SVM) is used for classification.

然后再以支持向量机(SVM)和最近邻分类法相结合组成分类器进行分类。

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Firstly KPCA is used to extract the features of human face image, and then SVM combined with the nearest distance rule is used for classification, which depends on the kernel principal components.

该方法首先利用核主元分析对人脸图像进行特征提取，然后依据支持向量机与最近邻准则对所提取的核主元特征进行分类识别。

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