We present a parallel algorithm for k-nearest neighbor graph construction that uses Morton ordering. Experiments show that our approach has the following advantages over existing methods: (1) Faster construction of k-nearest neighbor graphs in practice on multi-core machines. (2) Less space usage. (3) Better cache efficiency. (4) Ability to handle large data sets. (5) Ease of parallelization an...

This paper proposed a new weighted KNN data filling algorithm based on grey correlation analysis (GBWKNN) by researching the nearest neighbor of missing data filling method. It is aimed at that missing data is not sensitive to noise data and combined with grey system theory and the advantage of the K nearest neighbor algorithm. The experimental results on six UCI data sets showed that its filli...

Nearest neighbor rule or k-nearest neighbor rule is a technique of nonparametric pattern recognition. Its algorithm is simple and error is smaller than twice the Bayes error if there are enough training samples. However, it requires enormous computational quantities that is proportional to the number of samples and the number of dimensions of feature vector. In this paper, a fast algorithm for ...