A Novel Machine Learning Model to Predict the Staying Time of International Migrants

Abstract

In this paper, a novel machine learning model is proposed to predict the staying time of international migrants. The competitive machine learning approaches which can be used to predict the staying time of international migrants suffer from hyper-attributes tuning and over-fitting issues. Therefore, a particle swarm optimization (PSO) based support vector machine (SVM) model is proposed to predict the staying time of international migrants. Extensive experiments are performed by considering the international migrants dataset to predict the staying time of international migrants. Experimental results illustrate that the proposed approach outperforms the existing machine learning approaches in terms of f-measure, accuracy, specificity, and sensitivity.