Computational efficiency is usually important for learning algorithms operating in AZD1981

Computational efficiency is usually important for learning algorithms operating in AZD1981 the “large p small n” setting. and bypasses the need for expensive tuning parameter optimization via cross-validation by employing Bayesian model averaging over the grid AZD1981 of tuning parameters. Additional computational efficiency is usually achieved by adopting the singular value decomposition re-parametrization of the… Continue reading Computational efficiency is usually important for learning algorithms operating in AZD1981