Before diving into linear regression, it’s essential to understand the broader concept of regression in machine learning. Regression analysis is a type of supervised learning where the goal is to predict a continuous target variable. This target variable can take on any value within a given range. Think of it as estimating a number instead of classifying something into categories (which is what classification algorithms do).
Examples of regression problems include:
- Predicting the price of a house based on its size, location, and age.
- Forecasting the daily temperature based on historical weather data.
- Estimating the number of website visitors based on marketing spend and time of year.