Elective Recommendation Support through K-Means Clustering Using R-Tool
Agnivesh, Rajiv Pandey · 2015
The data generated from both men and machines are exponentially multiplying the size and the structural definition of the data. Such a voluminous, dynamic and unstructured data termed as Big Data is analyzed and maintained and can be used for various purposes and applications. Big Data is generated from sources like social media, cyber physical system and business entities. This enormous data generation leads to problems of data storage and analysis. The Big Data with its diverse features calls for various tools, technologies and algorithms to make an inference which shall render strategically advantage to any entity. A typical data analytical scenario is a multidimensional problem and data clustering can lead to multi spatial analysis. Cluster can be a result of various algorithms. In this paper k means clustering is applied to generate clusters using R statistical tool and recommend elective on the basis of student's performance.