Prediction of Depression among Senior Citizens using Machine Learning Classifiers

Depression among elderly population is an emerging problem of public health. Various socio demographic factors like age, sex, earning status, living spouse and family type etc are responsible for depression among senior people. Some co morbid conditions like visual problem, hearing difficulties, mobility problem also influence the disease. But depression can be diagnosed at earliest using predictive modeling with various influencing input variables. WEKA is a data mining tool used for prediction based on machine learning classifiers. In this paper five machine learning classifiers are compared with respect to three test options. A best method for depression prediction in aged persons also has been chosen among these five methods through comparison study. General Terms Machine learning algorithm, Depression, Senior Citizens.