Data Mining: A Comparative Study of its Various Techniques and its Process

Marie Fernandes¹

Section:Review Paper, Product Type: Isroset-Journal
Vol.5 , Issue.1 , pp.19-23, Feb-2017

Online published on Feb 28, 2017

Copyright © Marie Fernandes . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Data Mining also called as Information Mining or certainty finding is the term which is utilized for removing or finding helpful data from the information that are available in vast databases. It likewise investigates covered up or prescient examples of content that can be said as predictive patterns of text, from databases. This term showed up in 1990`s. It is a procedure that examines or analyses information from alternate points of view and compresses it into helpful data. This data can then be utilized for different business purposes by various undertakings. Information mining from that point forward has turned into an essential piece of Knowledge Discovery in Databases (KDD), data Digging, data fishing, and Data Collecting as appropriately termed as Data Dredging, Data Fishing, and Information Harvesting. It turns a large collection of data into knowledge that can fulfill current global challenge because computerization has lead to explosively growing, widely available and gigantic body of data floating through WWW. Data mining methods are expected to change this information into sorted out learning. Keeping in mind the end goal to do as such; capable and flexible tools are required which would reveal important data from the huge measures of information. This need has prompted to numerous strategies, for example, Classical Techniques which incorporates Statistics which provides measurements, Neighborhoods and Clustering which works through grouping and the Cutting edge Procedures incorporates Trees, Networks and Rules. The dominant part of information mining methods manages distinctive information sorts. The scope, purpose and motivation behind this paper is to do a relative investigation of the different procedures accessible in information mining with their preferences, burdens and the field where they can be properly utilized. This paper presents overview of data mining, the different strategies of data or information mining.

Key-Words / Index Term :
Data mining, Data Dredging, Statistics, Nearest Neighbor, Decision Trees and Neural Networks

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