@article{(Open Science Index):https://publications.waset.org/pdf/10006640,
	  title     = {Building a Scalable Telemetry Based Multiclass Predictive Maintenance Model in R},
	  author    = {Jaya Mathew},
	  country	= {},
	  institution	= {},
	  abstract     = {Many organizations are faced with the challenge of how to analyze and build Machine Learning models using their sensitive telemetry data. In this paper, we discuss how users can leverage the power of R without having to move their big data around as well as a cloud based solution for organizations willing to host their data in the cloud. By using ScaleR technology to benefit from parallelization and remote computing or R Services on premise or in the cloud, users can leverage the power of R at scale without having to move their data around.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {11},
	  number    = {3},
	  year      = {2017},
	  pages     = {365 - 370},
	  ee        = {https://publications.waset.org/pdf/10006640},
	  url   	= {https://publications.waset.org/vol/123},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 123, 2017},
	}