k-Nearest Neighbour (KNN) is one of the most popular algorithms for pattern recognition and data classification, but the traditional KNN classification method has some disadvantages. In this paper, aim at the KNN classification method's limitation, we proposed a hybrid intelligent classification algorithm. This novel algorithm combined the particle swarm optimisation algorithm and weighted KNN algorithm to improve classification performance. The experimental results show that our proposed algorithm outperforms the traditional KNN method with greater accuracy.
|Number of pages||8|
|Journal||International Journal of Wireless and Mobile Computing|
|State||Published - Dec 4 2013|
- Data classification
- K-nearest neighbour
- Particle swarm optimisation
- Weighted k-nearest neighbour