Polynomial regression
Polynomial regression is a form of Regression analysis that models the relationship between a dependent variable and one or more independent variables using a polynomial equation of a specified degree. This technique is often used in Data analysis and Machine learning to fit complex, non-linear relationships between variables. The polynomial equation can be of any degree, but higher degrees can lead to Overfitting, where the model becomes too complex and starts to fit the Noise in the data rather than the underlying pattern. Richard Feynman and other statisticians have discussed the importance of balancing model complexity with Evaluation and Credibility. Polynomial regression is closely related to other techniques such as Linear regression and can be used in a variety of fields, including Economics, Biology, and Social sciences.