In my machine learning analysis on US Census salary data, my goal was to regress two factor income levels: "<= $50K" and "> $50K". The objective was to build a predictive model and identify the most critical variables that determine annual income thresholds. By training the model on the dataset, I aimed to uncover patterns and understand the relationship between various factors and income levels. Among the most effective variables were marital status, age, and capital gains. This analysis provides valuable insights into the predictors of income in the US Census dataset Noteworthy variables that demonstrated significant impact are:
Marital Status Age Capital Gains