L. Sriram, S. Lavanya, K. Vishnu, Anna University Regional Centre, Coimbatore, Tamilnadu, India.
DOI : 01.0401/ijaict.2014.01.04
International Journal of Advanced Information and Communication Technology
Received On : March 12, 2018
Revised On : April 15, 2018
Accepted On : May 10, 2018
Published On : June 05, 2018
Volume 05, Issue 06
Pages : 877-880
Abstract
Class imbalance problems have drawn increasing interest lately because of its classification trouble caused by imbalanced class distributions and poor prediction performance for minority class. Many ensemble approaches only concentrated on two-class imbalance problems. There are many unresolved concerns in multiclass imbalanced problems. Using One-vs-One binarization technique for decomposing the original multiclass data-set into binary classification problems. Then, whenever each one of these binary sub problems is imbalanced, applying undersampling step, using the ACOsampling algorithm in order to rebalance the data. Only taking out high frequency dataset from majority samples and mix those with all minority samples to build the final balanced training set. Lastly, evaluate the method on four benchmarks skewed DNA microarray dataset by support vector machine (SVM) Classifier.
Keywords
Multi-class classification, Binarization, SVM, Imbalance data, One-vs-One, Undersampling, Ant Colony Optimization.
Cite this article
L. Sriram, S. Lavanya, K. Vishnu, “Imbalanced Multiclass Data Classification using Ant Colony Optimization Algorithm ” INTERNATIONAL JOURNAL OF ADVANCED INFORMATION AND COMMUNICATION TECHNOLOGY, pp.877-880, June 05, 2018.
Copyright
© 2018 L. Sriram, S. Lavanya, K. Vishnu. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.