Efficient Algorithm of Canopy-Kmeans Based on Hadoop Platform
Qin Zhao · Electronic Science and Technology · 2014
This paper studies MapReduce programming model under the Hadoop platform,analyzes the advantages and the disadvantages of traditional Kmeans and Canopy algorithms,and then proposes an improved Kmeans algorithm based on Canopy. The minimum maximum principle is used to improve the randomicity problem of Canopy-Kmeans algorithm to avoid the blindness of Cannopy. The MapReduce parallel programming method is carried out in massive news aggregation. The experiments show that this method has higher accuracy and stability than the traditional Kmeans and Canopy algorithms.