FOCUS-RRK FEATURE SELECTION TECHNIQUE FOR ENHANCING THE ACCURACY IN SOCIAL NETWORK DATA
Journal Title: World Journal of Engineering Research and Technology - Year 2017, Vol 3, Issue 1
Abstract
Feature Selection is an effective technique in reducing the dimensionality of features in many applications where Online Social Network’s datasets involve hundreds or thousands of features. The raw data are usually with inferior qualities such as redundancy and unreliability. Mining raw data for a given task has proved to be deteriorating in efficiency. There are many algorithms in data mining which can be used in dealing with redundant or missing data. Before the mining process begins those instances with missing value are considered insignificant to the result and thus can be eliminated from the dataset. The purpose of this research paper is twofold: Identifying and removing the redundant features with their latest solutions for Consistency Measure in an Online Social Network.
Authors and Affiliations
Rajkumar Ramasamy
Keywords
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