MapReduce-Based Parallel Linear Regression for Face Recognition

Li Sheng Zhang; Hua Yong Liu; Da Jiang Lei

doi:10.4028/www.scientific.net/AMM.556-562.2628

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562MapReduce-Based Parallel Linear Regression for...

MapReduce-Based Parallel Linear Regression for Face Recognition

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

2628-2632

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.2628

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Online since:

May 2014

Authors:

Li Sheng Zhang*, Hua Yong Liu, Da Jiang Lei

Keywords:

Face Recognition, Linear Regression, MapReduce Programming Mode, Parallel Computing

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* - Corresponding Author

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