IJFANS International Journal of Food and Nutritional Sciences

ISSN PRINT 2319 1775 Online 2320-7876

Automatic Detection of Money donors using Supervised Machine Learning Models

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Naresh Vurukonda1,V.Vidyasagar2
» doi: 10.48047/IJFANS/11/S7/007

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.

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