Rotation of random forests for genomic and proteomic classification problems.

Abstract

Random Forests have been recently widely used for different kinds of classification problems. One of them is classification of gene expression samples that is known as a problem with extremely high dimensionality, and therefore demands suited classification techniques. Due to its strong robustness with respect to large feature sets, Random Forests show… (More)
DOI: 10.1007/978-1-4419-7046-6_21

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