Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
To facilitate more meaningful interpretation considering the internal interdependency relationships between data values, a new form of high-order (multiple-valued) pattern known a...
In the last decades, a large family of algorithms supervised or unsupervised; stemming from statistic or geometry theory have been proposed to provide different solutions to the p...
A relevance filter is proposed which removes features based on the mutual information between class labels and features. It is proven that both feature independence and class condi...
Background: A major goal of the analysis of high-dimensional RNA expression data from tumor tissue is to identify prognostic signatures for discriminating patient subgroups. For t...
Birte Hellwig, Jan G. Hengstler, Marcus Schmidt, M...