Assumptions of Linear Regression - Search Videos

When linear regression lies: the assumptions | ML interview

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When linear regression lies: the assumptions | ML interview

A high R-squared can hide a model that's broken in four different ways. Linear regression rests on assumptions, linearity, independent errors, constant variance, and roughly normal residuals, and when they break the coefficients lie. The fit minimizes squared error no matter what, so it'll draw a confident line through data that isn't linear at ...

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