MLSeq-package {MLSeq}R Documentation

Machine learning interface for RNA-Seq data

Description

This package applies machine learning methods, such as Support Vector Machines (SVM), Random Forest (RF), Classification and Regression Trees (CART), Linear Discriminant Analysis (LDA) and more to RNA-Seq data. MLSeq combines well-known differential expression algorithms from bioconductor packages with functions from a famous package caret, which has comprehensive machine learning algorithms for classification and regression tasks. Although caret has 200+ classification/regression algorithm built-in, approximately 85 classification algorithms are used in MLSeq for classifying gene-expression data. See availableMethods() for further information.

Author(s)

Gokmen Zararsiz, Dincer Goksuluk, Selcuk Korkmaz, Vahap Eldem, Bernd Klaus, Ahmet Ozturk and Ahmet Ergun Karaagaoglu

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Maintainers:

Gokmen Zararsiz, gokmenzararsiz@erciyes.edu.tr

Dincer Goksuluk dincer.goksuluk@hacettepe.edu.tr

Selcuk Korkmaz selcukorkmaz@hotmail.com

See Also

availableMethods, getModelInfo

Package: MLSeq
Type: Package
License: GPL (>= 2)

[Package MLSeq version 2.2.0 Index]