Capturing Curves: Advanced Modeling with Polynomial Regression
When we analyze relationships between variables in machine learning, we often find that a straight line doesn’t tell the whole story. That’s where polynomial transformations come in, adding layers to our regression models without complicating the calculation process. By transforming our features into their polynomial counterparts—squares, cubes, and other higher-degree terms—we give linear models the flexibility to curve and twist, fitting snugly to the underlying trends of our data.
This blog post will explore how we can move beyond simple linear models to capture more complex relationships in our data. You’ll learn about the power of polynomial and cubic regression techniques, which allow us to see beyond the apparent and uncover the underlying patterns that a straight line might