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== RTextTools - A Supervised LearningPackage for Text Classification ==
 
http://www.rtexttools.com/
 
  
The '''''train_model()''''' function takes each algorithm, one by one, to produce an object passable to '''''classify_model().'''''
 
 
 
A convenience '''''train_models()''''' function trains all models at once by passing in a vector of model requests. The syntax below demonstrates model creation for all nine algorithms:
 
{| class="wikitable"
 
|+
 
!Algorithms
 
!Author
 
!From package
 
!Keyword
 
!Comment
 
!
 
|-
 
|Support vector machine
 
|[https://cran.r-project.org/web/packages/e1071/index.html Meyer et al., 2012]
 
|
 
|SVM
 
|Low-memory algorithms
 
|
 
|-
 
|Glmnet
 
|Friedman et al., 2010
 
|
 
|GLMNET
 
|Low-memory algorithms
 
|
 
|-
 
|Maximum entropy
 
|Jurka, 2012
 
|
 
|MAXENT
 
|Low-memory algorithms
 
|
 
|-
 
|Scaled linear discriminant analysis
 
|[https://cran.r-project.org/web/packages/ipred/index.html Peters and Hothorn, 2012]
 
|[https://cran.r-project.org/web/packages/ipred/index.html ipred]
 
|SLDA
 
|
 
|
 
|-
 
|Bagging
 
|[https://cran.r-project.org/web/packages/ipred/index.html Peters and Hothorn, 2012]
 
|[https://cran.r-project.org/web/packages/ipred/index.html ipred]
 
|BAGGING
 
|
 
|
 
|-
 
|Boosting
 
|[https://cran.r-project.org/web/packages/caTools/index.html Tuszynski, 2012]
 
|[https://cran.r-project.org/web/packages/caTools/index.html caTools]
 
|BOOSTING
 
|
 
|
 
|-
 
|Random forest
 
|[https://cran.r-project.org/web/packages/randomForest/index.html Liawand Wiener, 2002]
 
|[https://cran.r-project.org/web/packages/randomForest/index.html randomForest]
 
|RF
 
|
 
|
 
|-
 
|Neural networks
 
|Venables and Ripley, 2002
 
|[https://cran.r-project.org/web/packages/nnet/index.html nnet]
 
|NNET
 
|
 
|
 
|-
 
|Classification or regression tree
 
|Ripley., 2012
 
|[https://cran.r-project.org/web/packages/tree/index.html tree]
 
|TREE
 
|
 
|
 
|}
 
GLMNET  <- train_model(container,"GLMNET")
 

Latest revision as of 22:25, 23 February 2026