Tag: linear-models

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Linear regression basicsLinear regression fits an affine function to predict a continuous target by minimizing squared residuals between predictions and observed values. In matrix form, ordinary least squares projects the target vector onto the column space of the design matrix, yielding the normal equations in the full-rank case.