structural risk minimization (SRM)

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An algorithm that balances two goals:

The desire to build the most predictive model (for example, lowest loss).
The desire to keep the model as simple as possible (for example, strong regularization).

For example, a function that minimizes loss+regularization on the training set is a structural risk minimization algorithm.

For more information, see http://www.svms.org/srm/.

Contrast with empirical risk minimization.