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MReC4.5: C4.5 Ensemble Classification with MapReduce

2012-7-1. 2. Outline. MotivationC4.5BaggingMapReduceMReC4.5EvaluationsConclusions. 2012-7-1. 3. Motivation. Classification plays an important role in data mining C4.5, one kind of decision tree classification algorithm known as landmark in data mining Ensemble learning mechanism is very suit

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MReC4.5: C4.5 Ensemble Classification with MapReduce

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    1. MReC4.5: C4.5 Ensemble Classification with MapReduce Gongqing Wu1, Haiguang Li1, Xuegang Hu1, Yuanjun Bi1, Jing Zhang1, Xindong Wu1, 2 1School of Computer Science and Information Engineering Hefei University of Technology, Hefei, China 2Department of Computer Science University of Vermont Burlington, U.S.A. Yantai, China, 7/1/2012

    2. 2012-7-1 2 Outline Motivation C4.5 Bagging MapReduce MReC4.5 Evaluations Conclusions

    3. 2012-7-1 3 Motivation Classification plays an important role in data mining C4.5, one kind of decision tree classification algorithm known as landmark in data mining Ensemble learning mechanism is very suitable for parallel and distributed computing model in nature MapReduce is a new distributed programming paradigm proposed by Google for the parallel and distributed processing on large data sets Offer an ensemble C4.5 classification method based on MapReduce, MReC4.5 Make MReC4.5 classifier “Construct Once, Use Anywhere” by providing a series of serialization operations on the model level.

    4. 2012-7-1 4 C4.5

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