Learning Markov Blanket Bayesian Network for Big Data in MapReduce

UM > Faculty of Science and Technology > DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE

Status	已發表Published
	Learning Markov Blanket Bayesian Network for Big Data in MapReduce
	Che, Y.; Hong, S.; Zhang, D.; Zhang, L.
	2017
Source Publication	Proceedings of Learning Markov Blanket Bayesian Network for Big Data in MapReduce
Abstract	A challenge task of data mining is to process massive data in the big data era. MapReduce is an attractive model to overcome this challenge. This paper presents a new method to accelerate the process of learning Markov blanket Bayesian network(MBBN). Markov blanket is a better model type of Bayesian network in some complex datasets. The time and space cost of learning Markov blanket is large, and grows fast as the variables increase. Large amounts of data are needed for its independence test which makes the problem harder. The statistical phase and independence test are parallelized to make it find an appropriate relation among variables in the MapReduce framework. Computational results are reported by testing four datasets and show that the speed-up can be obtained by means of MapReduce. In particular, the Markov blanket in MapReduce has higher accuracy rate than naïve Bayesian and tree-augmented naïve Bayesian澢
Keyword	Big Data MapReduce Bayesian Network Markov blanket Data Mining
URL	View the original
Language	英語English
The Source to Article	PB_Publication
PUB ID	40353
Document Type	Conference paper
Collection	DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Recommended Citation GB/T 7714	Che, Y.,Hong, S.,Zhang, D.,et al. Learning Markov Blanket Bayesian Network for Big Data in MapReduce[C], 2017.
APA	Che, Y.., Hong, S.., Zhang, D.., & Zhang, L. (2017). Learning Markov Blanket Bayesian Network for Big Data in MapReduce. Proceedings of Learning Markov Blanket Bayesian Network for Big Data in MapReduce.

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