R语言Caret中train支持的method

可以使用以下代码查看

library(caret)
names(getModelInfo())
> names(getModelInfo())
  [1] "ada"                 "AdaBag"              "AdaBoost.M1"        
  [4] "adaboost"            "amdai"               "ANFIS"              
  [7] "avNNet"              "awnb"                "awtan"              
 [10] "bag"                 "bagEarth"            "bagEarthGCV"        
 [13] "bagFDA"              "bagFDAGCV"           "bam"                
 [16] "bartMachine"         "bayesglm"            "binda"              
 [19] "blackboost"          "blasso"              "blassoAveraged"     
 [22] "bridge"              "brnn"                "BstLm"              
 [25] "bstSm"               "bstTree"             "C5.0"               
 [28] "C5.0Cost"            "C5.0Rules"           "C5.0Tree"           
 [31] "cforest"             "chaid"               "CSimca"             
 [34] "ctree"               "ctree2"              "cubist"             
 [37] "dda"                 "deepboost"           "DENFIS"             
 [40] "dnn"                 "dwdLinear"           "dwdPoly"            
 [43] "dwdRadial"           "earth"               "elm"                
 [46] "enet"                "evtree"              "extraTrees"         
 [49] "fda"                 "FH.GBML"             "FIR.DM"             
 [52] "foba"                "FRBCS.CHI"           "FRBCS.W"            
 [55] "FS.HGD"              "gam"                 "gamboost"           
 [58] "gamLoess"            "gamSpline"           "gaussprLinear"      
 [61] "gaussprPoly"         "gaussprRadial"       "gbm_h2o"            
 [64] "gbm"                 "gcvEarth"            "GFS.FR.MOGUL"       
 [67] "GFS.LT.RS"           "GFS.THRIFT"          "glm.nb"             
 [70] "glm"                 "glmboost"            "glmnet_h2o"         
 [73] "glmnet"              "glmStepAIC"          "gpls"               
 [76] "hda"                 "hdda"                "hdrda"              
 [79] "HYFIS"               "icr"                 "J48"                
 [82] "JRip"                "kernelpls"           "kknn"               
 [85] "knn"                 "krlsPoly"            "krlsRadial"         
 [88] "lars"                "lars2"               "lasso"              
 [91] "lda"                 "lda2"                "leapBackward"       
 [94] "leapForward"         "leapSeq"             "Linda"              
 [97] "lm"                  "lmStepAIC"           "LMT"                
[100] "loclda"              "logicBag"            "LogitBoost"         
[103] "logreg"              "lssvmLinear"         "lssvmPoly"          
[106] "lssvmRadial"         "lvq"                 "M5"                 
[109] "M5Rules"             "manb"                "mda"                
[112] "Mlda"                "mlp"                 "mlpKerasDecay"      
[115] "mlpKerasDecayCost"   "mlpKerasDropout"     "mlpKerasDropoutCost"
[118] "mlpML"               "mlpSGD"              "mlpWeightDecay"     
[121] "mlpWeightDecayML"    "monmlp"              "msaenet"            
[124] "multinom"            "mxnet"               "mxnetAdam"          
[127] "naive_bayes"         "nb"                  "nbDiscrete"         
[130] "nbSearch"            "neuralnet"           "nnet"               
[133] "nnls"                "nodeHarvest"         "null"               
[136] "OneR"                "ordinalNet"          "ordinalRF"          
[139] "ORFlog"              "ORFpls"              "ORFridge"           
[142] "ORFsvm"              "ownn"                "pam"                
[145] "parRF"               "PART"                "partDSA"            
[148] "pcaNNet"             "pcr"                 "pda"                
[151] "pda2"                "penalized"           "PenalizedLDA"       
[154] "plr"                 "pls"                 "plsRglm"            
[157] "polr"                "ppr"                 "PRIM"               
[160] "protoclass"          "qda"                 "QdaCov"             
[163] "qrf"                 "qrnn"                "randomGLM"          
[166] "ranger"              "rbf"                 "rbfDDA"             
[169] "Rborist"             "rda"                 "regLogistic"        
[172] "relaxo"              "rf"                  "rFerns"             
[175] "RFlda"               "rfRules"             "ridge"              
[178] "rlda"                "rlm"                 "rmda"               
[181] "rocc"                "rotationForest"      "rotationForestCp"   
[184] "rpart"               "rpart1SE"            "rpart2"             
[187] "rpartCost"           "rpartScore"          "rqlasso"            
[190] "rqnc"                "RRF"                 "RRFglobal"          
[193] "rrlda"               "RSimca"              "rvmLinear"          
[196] "rvmPoly"             "rvmRadial"           "SBC"                
[199] "sda"                 "sdwd"                "simpls"             
[202] "SLAVE"               "slda"                "smda"               
[205] "snn"                 "sparseLDA"           "spikeslab"          
[208] "spls"                "stepLDA"             "stepQDA"            
[211] "superpc"             "svmBoundrangeString" "svmExpoString"      
[214] "svmLinear"           "svmLinear2"          "svmLinear3"         
[217] "svmLinearWeights"    "svmLinearWeights2"   "svmPoly"            
[220] "svmRadial"           "svmRadialCost"       "svmRadialSigma"     
[223] "svmRadialWeights"    "svmSpectrumString"   "tan"                
[226] "tanSearch"           "treebag"             "vbmpRadial"         
[229] "vglmAdjCat"          "vglmContRatio"       "vglmCumulative"     
[232] "widekernelpls"       "WM"                  "wsrf"               
[235] "xgbDART"             "xgbLinear"           "xgbTree"            
[238] "xyf"  

关于每个缩写具体对应哪个模型,也可以查看详细说明

使用lm的情况

a=train(cmedv~.,data=w,method="lm")

关于其他方面的细节可以查看详细的参数说明

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