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| − | The '''''train_model()''''' function takes each algorithm, one by one, to produce an object passable to '''''classify_model().'''''
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| − | 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:
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| − | {| class="wikitable"
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| − | |+
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| − | !Algorithms
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| − | !Author
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| − | !From package
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| − | !Keyword
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| − | !Comment
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| − | !
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| − | |-
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| − | |Support vector machine
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| − | |[https://cran.r-project.org/web/packages/e1071/index.html Meyer et al., 2012]
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| − | |SVM
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| − | |Low-memory algorithms
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| − | |
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| − | |-
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| − | |Glmnet
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| − | |Friedman et al., 2010
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| − | |GLMNET
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| − | |Low-memory algorithms
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| − | |-
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| − | |Maximum entropy
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| − | |Jurka, 2012
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| − | |MAXENT
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| − | |Low-memory algorithms
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| − | |-
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| − | |Scaled linear discriminant analysis
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| − | |Peters and Hothorn, 2012
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| − | |ipred
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| − | |SLDA
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| − | |
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| − | |
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| − | |-
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| − | |Bagging
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| − | |Peters and Hothorn, 2012
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| − | |ipred
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| − | |BAGGING
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| − | |-
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| − | |Boosting
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| − | |Tuszynski, 2012
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| − | |caTools
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| − | |BOOSTING
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| − | |
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| − | |-
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| − | |Random forest
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| − | |Liawand Wiener, 2002
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| − | |randomForest
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| − | |RF
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| − | |
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| − | |
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| − | |-
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| − | |Neural networks
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| − | |Venables and Ripley, 2002
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| − | |nnet
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| − | |NNET
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| − | |-
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| − | |Classification or regression tree
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| − | |Ripley., 2012
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| − | |tree
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| − | |TREE
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| − | |}
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| − | GLMNET <- train_model(container,"GLMNET")
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