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Introduction to Linear Regression: Exploring the Secrets of Prediction
Linear regression is a fundamental machine learning algorithm used for predicting a continuous outcome based on one or more input features. It assumes a linear relationship between the input features and the target variable, making it easy to interpret and implement. Visit the detailed tutorial here.
Types of Linear Regression
There are two main types of linear regression:
Simple Linear Regression
Simple linear regression models the relationship between one independent variable and the dependent variable using a linear equation. For example, predicting house prices based on square footage.
Multiple Linear Regression
Multiple linear regression models the relationship between multiple independent variables and the dependent variable using a linear equation. Predicting house prices based on square footage, number of bedrooms, and location.
