Model selection is an important ingredient of many machine learning algorithms, in particular when the sample size in small, in order to strike the right trade-off between overfitt...
We address feature selection problems for classification of small samples and high dimensionality. A practical example is microarray-based cancer classification problems, where sa...
We examine the learning-curve sampling method, an approach for applying machinelearning algorithms to large data sets. The approach is based on the observation that the computatio...
Background: Currently real time PCR is the most precise method by which to measure gene expression. The method generates a large amount of raw numerical data and processing may no...
Data collection for both training and testing a classifier is a tedious but essential step towards face detection and recognition. It is a piece of cake to collect more than hundre...