Work place: FET (CSE), MRIU, Faridabad
E-mail: veena.mittal06@gmail.com
Website:
Research Interests: Data Mining, Data Structures and Algorithms, Analysis of Algorithms
Biography
Veena Tayal received her B.Tech degree in Computer Science from Guru Jambheshwar University of Science & Technology, Hisar in 2007. She received her M. Tech degree in Computer Science from Banasthali University, Rajasthan in 2009. She is a Research Scholar in the Faculty of Engineering at the Manav Rachna International University, Faridabad. She is presently pursuing her doctorate degree in Computer Science under the guidance of Dr. Indu Kashyap. Her research interests include data mining, concept drift, outlier analysis in data streams.
DOI: https://doi.org/10.5815/ijisa.2016.12.08, Pub. Date: 8 Dec. 2016
In the real world, most of the applications are inherently dynamic in nature i.e. their underlying data distribution changes with time. As a result, the concept drifts occur very frequently in the data stream. Concept drifts in data stream increase the challenges in learning as well, it also significantly decreases the accuracy of the classifier. However, recently many algorithms have been proposed that exclusively designed for data stream mining while considering drifting concept in the data stream.This paper presents an empirical evaluation of these algorithms on datasets having four possible types of concept drifts namely; sudden, gradual, incremental, and recurring drifts.
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