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B0520
Title: Estimating the VC dimension with applications to model selection Authors:  Bertrand Clarke - University of Nebraska at Lincoln (United States) [presenting]
Merlin Mpoudeu - Bank of America (United States)
Abstract: An objective function is derived 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 several other model selection techniques. We do this for simulated data, two benchmark data sets, and data from a designed agronomic experiment.