Introduction to Classification

While regression predicts numbers, classification predicts categories. Will a customer churn? Is this email spam? What species is this flower?

Regression vs Classification

Binary vs Multi-class Classification

How Classification Works

Decision Boundaries

Classification creates invisible lines (or curves) that separate classes.

Common Classification Algorithms

Probability Predictions

Classification models can output probabilities, not just class labels.

The Classification Workflow

Key Takeaways

• Classification predicts discrete categories instead of numbers
• Binary classification has 2 classes; multi-class has 3+
• Models learn decision boundaries that separate classes
• Predictions can include probabilities for each class
• The workflow is similar to regression: prepare → train → predict → evaluate
• Common metrics: accuracy, precision, recall, F1-score (more in Module 7)

Next, we'll learn Logistic Regression - despite its name, it's for classification!