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Structural risk minimization

Structural risk minimization (SRM) is an inductive principle of use in machine learning. Commonly in machine learning, a generalized model must be selected from a finite data set, with the consequent problem of overfitting – the model becoming too strongly tailored to the particularities of the training set and generalizing poorly to new data. The SRM…

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Structural risk minimization

Nodes7
Edges6
Triples1
Avg. degree1.71
Density0.285714
Components1

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Structural risk minimization

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Structural risk minimization → Structural

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displaystyle data model training error lambda term regularization srm principle problem weights structural risk minimization learning overfitting machine set first

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SubjectPredicateObjectConfidenceSrc
Structural risk minimizationrelated to External linksStructural0.60section

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