An efficient weighted nearest neighbour classifier using vertical data representation

: The k-nearest neighbour (KNN) technique is a simple yet effective method for classification. In this paper, we propose an efficient weighted nearest neighbour classification algorithm, called PINE, using vertical data representation. A metric called HOBBit is used as the distance metric. The PINE algorithm applies a Gaussian podium function to set weights to different neighbours. We compare PINE with classical KNN methods using horizontal and vertical representation with different distance metrics. The experimental results show that PINE outperforms other KNN methods in terms of classification accuracy and running time. 

• Type: Journal
• Year: 2007
• Where: IJBIDM
• Authors: William Perrizo, Qin Ding, Maleq Khan, Anne Denton, Qiang Ding
• Keywords: IJBIDM 2007, KNN Methods, Neighbour Classification Algorithm, PINE