Model selection with Bayesian error estimator (also Python implementation available). This is an implementation of the parametric Bayesian Error Estimator for model selection purposes. In small-sample scenarios using parametric Bayesian error estimator can reduce the variance of the typical cross-validation based non-parametric error estimates. Also, it is fast to compute.
H. Huttunen, and J. Tohka . Model Selection for Linear Classifiers using Bayesian Error Estimation. Pattern Recognition , 48(11): 3739 - 3748, 2015. [Preprint] [Software]