Hyperparameter optimization: Difference between revisions

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| pmid = 29234465
| doi = 10.1186/s13040-017-0155-3
| pmc= 5721660}}</ref>
| doi-access = free
}}</ref>
 
Since the parameter space of a machine learner may include real-valued or unbounded value spaces for certain parameters, manually set bounds and discretization may be necessary before applying grid search.
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| last3 = Leyton-Brown
| first3 = Kevin
| titlechapter = Sequential modelModel-basedBased optimizationOptimization for generalGeneral algorithmAlgorithm configurationConfiguration
| journaltitle = Learning and Intelligent Optimization
| volume = 6683
| pages = 507–523