In this lesson, you'll use stratified random sampling to select proportionate samples from categorical data. You'll also understand the confusion matrix, its relation to the ROC curve, and why it's a better success metric than R squared for classifier algorithms. Finally, you'll build and finalize a machine learning classifier from start to finish.