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Canopy-kmeans efficient algorithm based on Hadoop platform

Source: Internet
Author: User
Keywords Hadoop
Tags advantages and disadvantages based hadoop platform programming programming method selection
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Canopy-kmeans efficient algorithm based on Hadoop platform

Zhaoqing

This paper introduces the programming model of MapReduce under Hadoop platform, analyzes the advantages and disadvantages of traditional clustering kmeans and canopy algorithm, and proposes an improved Kmeans algorithm based on canopy. Aiming at the stochastic problem of canopy selection in Canopy-kmeans algorithm, the algorithm is improved by the principle of minimum maximum, which avoids the blindness of cannopy selection. Using MapReduce parallel Programming method, mass news information clustering is used as the background. Experimental results show that this method has higher accuracy and stability compared with traditional kmeans and canopy algorithms.


Canopy-kmeans efficient algorithm based on Hadoop platform

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