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R Libraries (【classification】 (【Tree models】 (randomForest (randomForest()…

- - - - randomForest()
      - importance()
  - - - ksvm()
    - - svm()
      - tune.svm()
  - - - train()
        
        [method]
        
        【Tree-based models】
        
        'treebag' : Bagged CART
        
        'adaboost' : Adaboost Classification Trees
        
        'AdaBag' : Bagged AdaBoost
        
        'bartMachine' : Bayesian Adaptive Regression Trees
        
        'ada' : Boosted Classification Trees
        
        'LogitBoost' : Boosted Logistic Regression
        
        'blackboost' : Boosted Tree
        
        'bstTree' : Boosted Tree
        
        'J48' : C4.5-like Trees
        
        'C5.0' : C5.0
        
        'rpart' : CART
        
        'rpart1SE' : CART
        
        'rpart2' : CART'
        
        'rpartScore' : CART or Ordinal Responses
        
        'chaid' : CHi-squared Automated Interaction Detection
        
        'ctree' : Conditional Inference Tree
        
        'ctree2' : Conditional Inference Tree
        
        'C5.0ost' : Cost-Sensitive C5.0
        
        'rpartCost' : Cost-Sensitive CART
        
        'deepboost' : DeepBoost
        
        'xgbTree' : eXtreme Gradient Boosting
        
        'gbm_h2o' : Gradient Boosting Machines
        
        'M5' : Model Tree
        
        'rotationForest' : Rotation Forest
        
        'rotationForestCp' : Rotation Forest
        
        'C5.0Tree': Single C5.0 Tree
        
        'gbm' : Stochastic Gradient Boosting
        
        'nodeHarvest' : Tree-Based Ensmbles
        
        'evtree' : Tree Models from Genetic Algorithms
      - predict()