2019
JMLR
JMLR 2019
Model Selection via the VC Dimension
Abstract
We derive an objective function that can be optimized to give an estimator for the Vapnik-Chervonenkis dimension for use in 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. [abs] [ pdf ][ bib ] © JMLR 2019. (edit, beta)
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— Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning
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Hot Topic Early Bird
— statistical learning