MLSeq-package {MLSeq} | R Documentation |
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.
Dincer Goksuluk, Gokmen Zararsiz, Selcuk Korkmaz, Vahap Eldem, Ahmet Ozturk and Ahmet Ergun Karaagaoglu
—————–
Maintainers:
Dincer Goksuluk dincer.goksuluk@hacettepe.edu.tr
Gokmen Zararsiz, gokmenzararsiz@erciyes.edu.tr
Selcuk Korkmaz selcukorkmaz@hotmail.com
availableMethods
, getModelInfo
Package: | MLSeq |
Type: | Package |
License: | GPL (>= 2) |