Decoding Dollars: Adult Census Income Prediction

Abstract

The Adult Census Income Prediction Project aims to develop a machine learning model to predict whether an individual's income exceeds $50,000 per year based on demographic and employment attributes from the U.S. Census Bureau's Adult dataset. This project involves several key steps, including data preprocessing, exploratory data analysis, feature engineering, model selection, and evaluation.

Various algorithms, such as Logistic Regression, KNeighbor Classifier,Decision Trees and Random Forests are tested and optimized using techniques like GridSearchCV to find the best hyperparameters. The final model's performance is evaluated using metrics like accuracy, precision, recall, and the F1-score. The goal is to provide insights into the factors influencing income levels and build a robust predictive model for practical applications in fields like economic planning and policy-making.¶