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LINEAR REGRESSION WITH R AND HADOOP.

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Podrobná bibliografie
Název:	LINEAR REGRESSION WITH R AND HADOOP.
Autoři:	OANCEA, Bogdan¹ bogdanoancea@univnt.ro
Zdroj:	International Conference: Challenges of the Knowledge Society (CKS). 2015, p1007-1012. 6p.
Témata:	Java programming language, Regression analysis, Open source software, Ruby (Computer program language), Python programming language
Abstrakt:	In this paper we present a way to solve the linear regression model with R and Hadoop using the Rhadoop library. We show how the linear regression model can be solved even for very large models that require special technologies. For storing the data we used Hadoop and for computation we used R. The interface between R and Hadoop is the open source library RHadoop. We present the main features of the Hadoop and R software systems and the way of interconnecting them. We then show how the least squares solution for the linear regression problem could be expressed in terms of map-reduce programming paradigm and how could be implemented using the Rhadoop library. [ABSTRACT FROM AUTHOR]
Databáze:	Supplemental Index

Popis
Abstrakt:	In this paper we present a way to solve the linear regression model with R and Hadoop using the Rhadoop library. We show how the linear regression model can be solved even for very large models that require special technologies. For storing the data we used Hadoop and for computation we used R. The interface between R and Hadoop is the open source library RHadoop. We present the main features of the Hadoop and R software systems and the way of interconnecting them. We then show how the least squares solution for the linear regression problem could be expressed in terms of map-reduce programming paradigm and how could be implemented using the Rhadoop library. [ABSTRACT FROM AUTHOR]
ISSN:	20687796