What are linear models in machine learning?

What are linear models in machine learning?

Linear models are algorithms that predict outcomes based on a linear relationship between input features and the target variable.

Can you give me an example of a linear model?

Sure! A common example is linear regression, which predicts a continuous outcome based on one or more predictor variables.

How do I evaluate the performance of a linear model?

You can evaluate a linear model's performance using metrics like Mean Squared Error (MSE) or R-squared.

What are the assumptions behind linear regression?

The main assumptions are linearity, independence, homoscedasticity, and normality of residuals.