Background: Classification studies using gene expression datasets are usually based on small numbers of samples and tens of thousands of genes. The selection of those genes that a...
Malik Yousef, Segun Jung, Louise C. Showe, Michael...
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Abstract - We discuss an ensemble-of-classifiers based algorithm for the missing feature problem. The proposed approach is inspired in part by the random subspace method, and in pa...
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...
—Stability (robustness) of feature selection methods is a topic of recent interest, yet often neglected importance, with direct impact on the reliability of machine learning syst...