Due to the large number of genes measured in a typical microarray dataset, feature selection plays an essential role in tumor classification. In turn, relevance and redundancy are ...
We present a novel approach to dealing with overfitting in black-box models. It is based on the leverages of the samples, i.e. on the influence that each observation has on the pa...
A central problem in learning is selection of an appropriate model. This is typically done by estimating the unknown generalization errors of a set of models to be selected from a...
There exists a large and growing number of proposed estimation methods but little conclusive evidence ranking one method over another. Prior effort estimation studies suffered fro...
Tim Menzies, Omid Jalali, Jairus Hihn, Daniel Bake...
: Amino acid changing mutations in proteins are contstrained by purifying selection and accumulate at different rates. We estimate evolutionary rates on multiple alignments of euka...