Abstract Background Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers by choosing classifier parameter values that minimize the CV error estimate. We have evaluated the validity of using the CV error estimate of the optimized classifier as an estimate of the true error... https://thesportsshopkingswinfordes.shop/product-category/sols/
Bias in error estimation when using cross-validation for model selection
Internet - 26 minutes ago zjvorwfjyjblWeb Directory Categories
Web Directory Search
New Site Listings