中文说明：适合于多分类问题，二分类问题。该源代码的测试数据为常用的数据Iris，测试结果显示该算法的分类正确率极高，能够达到98%。K-最近邻(k-Nearest Neighbour，KNN)分类算法，是一个理论上比较成熟的方法，也是最简单的机器学习算法之一。该方法的思路是：如果一个样本在特征空间中的k个最相似(即特征空间中最邻近)的样本中的大多数属于某一个类别，则该样本也属于这个类别。
English Description：
It is suitable for multi classification problem and two classification problem. The test data of the source code is iris, and the test results show that the classification accuracy of the algorithm is very high, which can reach 98%. K-nearest neighbor (KNN) classification algorithm is a mature method in theory and one of the simplest machine learning algorithms. The idea of this method is: if most of the k most similar samples in the feature space belong to a certain category, then the sample also belongs to this category.