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 […]
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