Polynomial Regression Method
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In this article, we provide a comprehensive explanation of the polynomial regression method. Polynomial regression serves as a powerful regression analysis technique that enables better understanding of relationships within datasets. By implementing this approach, we can enhance trend forecasting capabilities and support improved decision-making processes. The method extends linear regression by adding polynomial terms (x², x³, etc.) to model nonlinear relationships, typically implemented using libraries like scikit-learn's PolynomialFeatures transformer combined with linear regression models. Key implementation steps include feature transformation, model fitting using least squares optimization, and evaluating fit quality through metrics like R-squared.
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