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The prominent inequality of wealth and income is a huge concern especially inthe United States. The likelihood of diminishing poverty is one valid reason toreduce the world's surging level of economic inequality. The principle ofuniversal moral equality ensures sustainable development and improve theeconomic stability of a nation. Governments in different countries have beentrying their best to address this problem and provide an optimal solution. Thisstudy aims to show the usage of machine learning and data mining techniques inproviding a solution to the income equality problem. The UCI Adult Dataset hasbeen used for the purpose. Classification has been done to predict whether aperson's yearly income in US falls in the income category of either greaterthan 50K Dollars or less equal to 50K Dollars category based on a certain setof attributes. The Gradient Boosting Classifier Model was deployed whichclocked the highest accuracy of 88.16%, eventually breaking the benchmarkaccuracy of existing works.

A Statistical Approach to Adult Census Income Level Prediction