Improved Canopy-Kmeans algorithm based on MapReduce
Dianhui Mao · Computer Engineering and Applications Journal · 2012
In order to solve the problem that how to void random Canopy selection of Canopy-Kmeans algorithm,this paper introduces an improved algorithm based on the minimum and maximum principle and realizes processing massive data based on MapReduce framework.Meanwhile,the algorithm is carried out in massive Internet news aggregation.The experiments show that the strategy of Canopy selection based on the minimum and maximum principle has higher classification accuracy and noise immunity compared to random strategy.