Incomplete Data Recovery Using Linear Regression

Hai Lin

doi:10.4028/www.scientific.net/AMM.571-572.642

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 571-572Incomplete Data Recovery Using Linear Regression

Incomplete Data Recovery Using Linear Regression

Abstract:

During the last few decades, there has been a lot of interest on systems using large amounts of data. In practice, not every piece of information is available, and people have to deal with incomplete data. There have been a lot models proposed for this problem. In this paper, we propose a new approach for incomplete data recovery. This new approach is based on linear regression. We do some experiments on real-world data and show that this new approach is appropriate for incomplete data recovery and can produce very good results.

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Periodical:

Applied Mechanics and Materials (Volumes 571-572)

Pages:

642-645

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.571-572.642

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Online since:

June 2014

Authors:

Hai Lin*

Keywords:

Data Recovery, Linear Regression

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* - Corresponding Author

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