How to Build a Naive Bayes Model

How to Build a Naive Bayes Model

This workflow shows how to build a simple Naive Bayes model. The workflow prepares the Adult dataset for machine learning by handling class imbalance (down-sampling to the minority class), and imputing missing values. The data is then split into training and testing sets, and a Naive Bayes model is trained to predict income and applied to the test data. Finally, the predictions are evaluated to measure how accurately the model classifies the income of an adult person.

Data Access

Data Preprocessing and Partitioning

Model Training and Testing

Model Evaluation