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Some Improvements in Tree Based Nearest Neighbour Search Algorithms

机译:基于树最近邻的搜索算法的一些改进

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Nearest neighbour search is one of the most simple and used technique in Pattern Recognition. In this paper we are interested on tree based algorithms that only make use of the metric properties of the space. One of the most known and refereed method in this class was proposed by Fukunaga and Narendra in the 70's. This algorithm uses a tree that is traversed on search time and uses some elimination rules to avoid the full exploration of the tree. This paper proposes two main contributions: two new ways for constructing the tree and two new elimination rules. As shown in the experiment section, both techniques reduce significantly the number of distance computations.
机译:最近的邻居搜索是模式识别中最简单且使用的技术之一。在本文中,我们对基于树的算法感兴趣,只能利用空间的度量属性。本课程中最着名和判决的方法之一是由70年代的福匈A和Narendra提出的。此算法使用在搜索时遍历的树,并使用一些消除规则来避免树的完整探索。本文提出了两个主要贡献:建造树的两种新方法和两个新的消除规则。如实验部分所示,这两种技术都减少了距离计算的数量。

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