生物识别：指纹、人脸、虹膜、头骨及静脉识别是最有应用价值的几个，本代码是静脉识别的C++代码，具有极高的参考价值。-Biometrics: fingerprint, face, iris, skull and intravenous application of recognition is the most a few, the vein identification code is C++ code, with a high reference value.

学习模式识别时候，会用到C均值处理一些数据。其中处理Iris数据是一个典型的问题，本例子由本人编写，为了完成其数据的分类。总共150个4维数据，将它分为三类。每个数据原归属于三类。-Learning pattern recognition when used C-means to deal with some data. Which deal with Iris data is a typical problem, the examples of which I am writing, in o

模式识别大作业K近邻算法（KNN）C++实现，内有iris和wine数据测试以及其他相关资料。-, Pattern Recognition large job K nearest neighbor algorithm (KNN) C++ achieved within the iris and wine data testing and other relevant information.

(1)Bayes分类 已知N=9， =3，n=2，C=3,问x= 应属于哪一类？ (2)聚类 使用c－均值聚类算法在IRIS数据上进行聚类分析 (3)鉴别分析 在ORL或Yale标准人脸数据库上完成模式识别任务。 用PCA与基于核的PCA（KPCA）方法完成人脸图像的重构与识别试验。-(1) Bayes classification Known N = 9, = 3, n = 2, C = 3, x = should ask which cat