Classification Modeling

Overview

Classification modeling predicts categorical target values, assigning observations to discrete classes or categories based on input features.

When to Use

• Predicting binary outcomes like customer churn, loan default, or email spam
• Classifying items into multiple categories such as product types or sentiment
• Building credit scoring models or risk assessment systems
• Identifying disease diagnosis or medical condition from patient data
• Predicting customer purchase likelihood or response to marketing
• Detecting fraud, anomalies, or quality defects in production systems

Classification Types

• Binary Classification: Two classes (yes/no, success/failure)
• Multiclass: More than two classes