What is the effect of using polynomial features in a linear regression model?
Practice Questions
Q1
What is the effect of using polynomial features in a linear regression model?
It reduces the model complexity
It can capture non-linear relationships
It increases the risk of underfitting
It eliminates multicollinearity
Questions & Step-by-Step Solutions
What is the effect of using polynomial features in a linear regression model?
Step 1: Understand that linear regression tries to find a straight line that best fits the data.
Step 2: Realize that some relationships between features (inputs) and the target variable (output) are not straight lines; they can be curved or more complex.
Step 3: Learn that polynomial features are created by taking existing features and raising them to a power (like squaring them or cubing them).
Step 4: Know that by adding these polynomial features to the model, it can fit curves instead of just straight lines.
Step 5: Conclude that using polynomial features helps the model better capture and understand non-linear relationships in the data.
