Model Selection via the VC-Dimension
classification
🧮 math.ST
stat.TH
keywords
modelselectionestimatorverifychervonenkiscomparedconsistentdata
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We derive an objective function that can be optimized to give an estimator of the Vapnik- Chervonenkis dimension for model selection in regression problems. We verify our estimator is consistent. Then, we verify it performs well compared to seven other model selection techniques. We do this for a variety of types of data sets.
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