MapReduce-Based Parallel Linear Regression for Face Recognition

In order to solve the problem of high time complexity of Linear Regression Classification algorithm,we propose a Mapreduce-based parallel linear regression classification algorithm. The map task uses the test image vector and the vector subspace to predict the response vector for one class, then cal...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 556-562; pp. 2628 - 2632
Main Authors Lei, Da Jiang, Zhang, Li Sheng, Liu, Hua Yong
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.05.2014
Subjects
MapReduce Programming Mode
Linear Regression
Face Recognition
Parallel Computing
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Summary:In order to solve the problem of high time complexity of Linear Regression Classification algorithm,we propose a Mapreduce-based parallel linear regression classification algorithm. The map task uses the test image vector and the vector subspace to predict the response vector for one class, then calculates the distance measure between the predicted response vectory and the original response vector. The reduce task processes the data which are generated by the mappers, the test image is assigned to the nearest class. The experiments shows that the MapReduce-based parallel linear regression classifier can significantly improve the efficiency of Face Recognition.
Bibliography:Selected, peer reviewed papers from the 2014 International Conference on Mechatronics Engineering and Computing Technology (ICMECT 2014), April 9-10, 2014, Shanghai, China
ISBN:3038351156
9783038351153
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.556-562.2628