An ensemble-based online learning algorithm for streaming data
Machine Learning
2017-04-27 v1
Abstract
In this study, we introduce an ensemble-based approach for online machine learning. The ensemble of base classifiers in our approach is obtained by learning Naive Bayes classifiers on different training sets which are generated by projecting the original training set to lower dimensional space. We propose a mechanism to learn sequences of data using data chunks paradigm. The experiments conducted on a number of UCI datasets and one synthetic dataset demonstrate that the proposed approach performs significantly better than some well-known online learning algorithms.
Cite
@article{arxiv.1704.07938,
title = {An ensemble-based online learning algorithm for streaming data},
author = {Tien Thanh Nguyen and Thi Thu Thuy Nguyen and Xuan Cuong Pham and Alan Wee-Chung Liew and James C. Bezdek},
journal= {arXiv preprint arXiv:1704.07938},
year = {2017}
}
Comments
19 pages, 3 figures