STUDY OF MULTICLASS CLASSIFICATION FOR IMBALANCED BIOMEDICAL DATA
Roshan M. Pote, Shrikant P. Akarte · 2014
In this paper an approach is introduced for more than two class classification which can combine more than two SVM classifiers. By combining the results which are obtained from various binary SVM classifiers, Multi-class classification is performed. the features are extracted, then the SVM methods are applied to the extracted feature set which are the unbalance in the dataset because they didn’t perform well [1] . This paper present an experimental results on multiple biomedical datasets show that the proposed solution can effectively cure the problem when the datasets are noisy and highly imbalanced.