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)

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

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Maintainers:

Dincer Goksuluk dincer.goksuluk@hacettepe.edu.tr

Gokmen Zararsiz, gokmenzararsiz@erciyes.edu.tr

Selcuk Korkmaz selcukorkmaz@hotmail.com

### See Also

`availableMethods`, `getModelInfo`

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

[Package MLSeq version 2.6.0 Index]