Automatic Detection of Money donors using Supervised Machine Learning Models

Abstract

Our goal is to correctly predict whether a given individual makes a profit of greater than 50,000 or less than 50,000 based on a set of attribute features which are already provided. So, with the data available we can come to conclusion that an individual can be a donor or not. And this model can help non-profit organizations which certainly depends on donation to correctly predict the donation that the organization has to request an individual based on the individual records. The is a hypothetical case study to identify potential donors to a charity that offers funding to people. It was found that every donor was making more than $50,000 annually. My task was to use machine learning algorithms to help this charity identify potential donors.