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This project encompasses exploratory data analysis and predictive modelling for income classification using a Random Forest Classifier. The dataset, loaded from a CSV file, contains diverse socio-economic features.
Details
.It employs advanced visualizations, including a correlation network, to uncover intricate feature relationships. After preprocessing and encoding,A Random Forest Classifier predicts income levels.