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Case Study III: Regression Analysis using Scalding and Spark

  • K G SrinivasaEmail author
  • Anil Kumar Muppalla
Chapter
  • 3.3k Downloads
Part of the Computer Communications and Networks book series (CCN)

Abstract

Regression analysis is usually applied to prediction and forecasting with substantial overlap with the field of machine learning. The relationship between the dependent and independent variables is determined through regression and to explore different forms of these relationships. In certain circumstances where the assumptions are restricted regression helps to infer a casual relationship. However, caution is advised as this can lead to illusions.

Keywords

Gradient Descent Implementation Detail Simple Application Sample Output Stochastic Gradient Descent 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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    Armstrong, J. Scott (2012). ”Illusions in Regression Analysis”. International Journal of Forecasting (forthcoming) 28 (3): 689Google Scholar
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    Bartlett, G., Stewart, J. D., Tamblyn, R., & Abrahamowicz, M. (1998). Normal distributions of thermal and vibration sensory thresholds. Muscle & nerve, 21(3), 367-374Google Scholar
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    Rencher, Alvin C., and William F. Christensen. Methods of multivariate analysis. Vol. 709. John Wiley & Sons, 2012Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.M.S. Ramaiah Institute of TechnologyBangaloreIndia

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