Ordinary least squares, or linear least squares, estimates the parameters in a regression model by minimizing the sum of the squared residuals.
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These are some of the Assumptions to be pondered while Applying Ordinary Least Square Method and Performing Regression Analysis.
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Analyse if the KPIs and the business objective of the model are achieved. If the parameters are not met, consider changing the model or improving the quality and quantity of the data.
Before deployment:
Polynomial regression is a unique case of linear regression:
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