A New Classifier for Handling Concept Drifting Data Stream

Ms. Rucha Patil , Mr. S.B. Chaudhary

Concept drift, stream data, classification, drift detection.

Concept drifting stream data mining have recently garnered a great deal of attention for Machine Learning Researcher. The major challenges in stream data mining are focused on speed of data arrival, changes in data distribution in certain time, storage capability that uses less memory, and adapting changes in small amount of time. In this paper, a new Classifier based on hybrid approach is proposed that handle concept drifting stream data. The proposed classifier is used Naives Bayes as base learner for classification of concept drifting stream data where as concept drift is detected and handled by using drift detection method.

Published Paper   E-Certificate

"A New Classifier for Handling Concept Drifting Data Stream", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.9, Issue 4, page no.1279 - 1283, April-2024, Available :https://ijsdr.org/papers/IJSDR2404187.pdf

Volume 9 Issue 4, April-2024

Pages : 1279 - 1283

Paper Reg. ID: IJSDR_211009

Published Paper Id: IJSDR2404187

Downloads: 000347405

Research Area: Computer Engineering 

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2404187

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2404187

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition