关键词: 分类, k 近邻算法, S 近邻算法, 分类准确率

Abstract: This paper studies classification techniques based on nearest-neighbor (NN), and designs a classification algorithm based on the shelly-NN (SNN) approach, which is without bias at selecting nearest neighbors. Traditional kNN classification and the SNN model are studied at the ideas of algorithm design and key techniques. Then they are also compared at the classification accuracy using several UCI data sets. Based on these researches, the paper gives the environment conditions suitable for the algorithms and analyzes the possible reasons. The results demonstrate that SNN algorithm is not sensitive to distance metrics and performs better at the classification accuracy on large data sets.

Key words: classification, k nearest neighbor algorithm, shelly nearest neighbor algorithm, classification accuracy