Machine learning with maximization (support) of separating margin (vector), called support
vector machine (SVM) learning, is a powerful classification tool that has been used for …

Microarray data classification is a difficult challenge for machine learning researchers due to
its high number of features and the small sample sizes. Feature selection has been soon …

Current benchmark reports of classification algorithms generally concern common classifiers
and their variants but do not include many algorithms that have been introduced in recent …

With the advent of high dimensionality, adequate identification of relevant features of the
data has become indispensable in real-world scenarios. In this context, the importance of …

Microarray gene expression data are often accompanied by a large number of genes and a
small number of samples. However, only a few of these genes are relevant to cancer …

Classification problems involving multiple classes can be addressed in different ways. One
of the most popular techniques consists in dividing the original data set into two-class …

In an era of growing data complexity and volume and the advent of big data, feature
selection has a key role to play in helping reduce high-dimensionality in machine learning …

Feature selection techniques have become an apparent need in many bioinformatics
applications. In addition to the large pool of techniques that have already been developed in …

Background Selection of relevant genes for sample classification is a common task in most
gene expression studies, where researchers try to identify the smallest possible set of genes …

The rapid advance of computer technologies in data processing, collection, and storage has
provided unparalleled opportunities to expand capabilities in production, services …