DISCOVERING HUMAN INFLUENZA VIRUS USING ENSEMBLE LEARNING

Abstract

Swine influenza is an infectious disease caused by one of the swine influenza viruses. The swine flu is also seen in humans and it is caused by human influenza viruses. Extracting useful information from virus protein sequences is an interesting research problem. Any changes in protein will alter the biological function and cause disease. The main objective of the research is to build a classification model that will discover the human influenza virus using its protein sequences through ensemble learning classifiers. A total of 404 protein sequences related to various types of human influenza virus were selected for our study. The classification models were built using ensemble learning techniques, such as bagging, boosting, voting, and forest of randomized trees. The accuracy of the classifiers was evaluated and the results were reported. Boosting and randomized trees classifiers were effective in recognizing the human influenza virus.