What is the interpretation for quadratic functions? I am working through the book Applied Predictive Modeling and came across something that was a bit confusing.

It discussed adding non linearity to a model to improve its fit - I get this part.

For example: $x^2 + 2x - 4$

What is the interpretation of these values though?

When we are using just a normal linear regression or a multivariate regression, we would say that the coefficients like 2 would suggest its relative importance relative to the other features being included in the model. However, what does this mean in the context of quadratic functions?

ie. Fuel efficiency of a car based on 2 Displacement + Displacement$^2$ -4

What exactly does displacement squared mean?

Any help would be greatly appreciated.

Thanks.
$Displacement$ component gives us a "line" to fit over the data points. To get more freedom add $Displacement^{2}$ a "curve" element. This adds to the flexibility - with same feature/ variable - to map the data points.
Please refer page 90, 91 on Introduction to Statistical Learning in R - Hastie, Tibshirani