一种近似的K最近邻图算法

一种近似的K最近邻图算法
邹蕾
【期刊名称】《江苏科技大学学报（自然科学版）》
【年(卷),期】2017(031)004
【摘要】针对K最近邻(KNN)图方法在数据挖掘和机器学习方面的问题,文中提出一种高效的基于K最近邻图的近似算法.首先随机生成一个KNN图近似值;对空间进行随意层次划分,构建一个近似近邻图,然后与KNN图近似值合并生成一个更准确的图;最后对生成的更准确的图进行近邻传播,进一步提高准确度.通过采用各种真实数据集和高维度合成数据进行实验研究,证实文中提出的算法性能优于先进的KNN图构造方法.%In view of the k-nearest neighbor (KNN) graph problems in data mining and machine learning, an efficient approximate algorithm is proposed based on the k-nearest neighbor graph.First, a random graph KNN approximation is generated;the space is divided at random level to construct an approximate nearest neighbor graph, and then approximate KNN value map they are combined to build a more accurate map;finally, neighbor propagation of the more accurate nearest neighbor graph further improves the accuracy.Experiments are performed by using real data sets and high-dimensional synthetic data, and the result shows that the proposed algorithm has better performance than the advanced KNN method.
【总页数】7页(P513-518,554)
【作者】邹蕾
【作者单位】吉林警察学院信息工程系,长春 130000
【正文语种】中文
【中图分类】TP393
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