Fast and informative model selection using learning curve cross-validation

HIGHLIGHTS

  • who: Felix, Mohr and Jan N., van Rijn from the (UNIVERSITY) have published the research: Fast and Informative Model Selection using Learning Curve Cross-Validation, in the Journal: (JOURNAL)
  • what: The work is based on observation-based learning curves rather than iteration-based curves, which are obtained from learner performance observations across iterations like in neural_networks . The experiments show that LCCV is on average more than 50% faster than vanilla crossvalidation, while usually choosing an equally performing algorithm configuration. The experiments show that the learning curves obtained using LCCV can be directly used to assert . . .

     

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