Poverty Classification of Central Perak Population Using Machine Learning

The issue of poverty has recently been brought to the public’s attention. The picture of Central Perak development reveals many families are not benefiting from national economic growth. Many families were still in poor category or status and hovering below the poverty line. The classification of the individual or of poor household in a class or poverty status can be a good instrument to focus on the living conditions of the poor. In this study, back propagation algorithm and other machine learning algorithm will be used to build models via anaconda using python programming language that can classify each poor household appropriate their poverty status. Network will be built using the weights of the selection of the best network. The best networks have been training on the sub-sub smaller dataset. By going through all the information provided by the experts who is in interested in this project and researching about this project and poverty of people and the difficulties they are facing in their daily life has become the backbone to propose this project paper to be developed into a prototype.