Supervised Learning

Supervised Learning Tasks

Regression: Used when the target variable is continuous (e.g. predicting house prices or stock market returns).

Regression: when the target variable we wish to predict is continuous - usually numeric.

Examples:

  • House Prices (in dollars)
  • Life Expectancy (in years)
  • Employee Salary (in dollars)
  • Distance to the Nearest Galaxy (in light years)

Classification: Used when the target variable is categorical (e.g. determining whether a transaction is fraudulent or not).

Classification: when the target variable we wish to predict is discrete - usually binary or categorical.

Examples:

  • Spam or Not (binary)
  • Success or Failure (binary)
  • Handwritten numeric digits (categorical)
  • 1-5 star rating scale (categorical???? )