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∑MathIntermediate

Pseudoinverse (Moore-Penrose)

The Moore–Penrose pseudoinverse generalizes matrix inversion to rectangular or singular matrices and is denoted A⁺.

#pseudoinverse#moore-penrose#least squares+12
∑MathIntermediate

Elastic Net Regularization

Elastic Net regularization combines L1 (Lasso) and L2 (Ridge) penalties to produce models that are both sparse and stable.

#elastic net#lasso
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#ridge regression
+12
∑MathIntermediate

L2 Regularization (Ridge/Weight Decay)

L2 regularization (also called ridge or weight decay) adds a penalty proportional to the sum of squared weights to discourage large parameters.

#l2 regularization#ridge regression#weight decay+12