A Fast KNN Algorithm Based on Simulated Annealing

K-Nearest Neighbor is used broadly in text classification, but it has one deficiency—computational efficiency. In this paper, we propose a heuristic search way to find out the k nearest neighbors quickly. Simulated annealing algorithm and inverted array are used to help find out the expected neighbors. Our experimental results demonstrate a significant improvement in classification computational efficiency in comparison with the conventional KNN.

• Type: Conference
• Year: 2007
• Where: DMIN
• Authors: Chuanyao Yang, Yuqin Li, Chenghong Zhang, Yunfa Hu
• Keywords: Classification Computational Efficiency, Data Mining, DMIN 2007, Heuristic Search Way, K-nearest Neighbor