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57-caret包支持训练的模型及其参数列表

57-caret包支持训练的模型及其参数列表

作者: wonphen | 来源:发表于2020-03-24 14:15 被阅读0次

    来源：http://topepo.github.io/caret/available-models.html

    模型 method 值 类型 依赖包 调优参数
    AdaBoost Classification Trees adaboost Classification fastAdaboost nIter, method
    AdaBoost.M1 AdaBoost.M1 Classification adabag, plyr mfinal, maxdepth, coeflearn
    Adaptive Mixture Discriminant Analysis amdai Classification adaptDA model
    Adaptive-Network-Based Fuzzy Inference System ANFIS Regression frbs num.labels, max.iter
    Adjacent Categories Probability Model for Ordinal Data vglmAdjCat Classification VGAM parallel, link
    Bagged AdaBoost AdaBag Classification adabag, plyr mfinal, maxdepth
    Bagged CART treebag Classification, Regression ipred, plyr, e1071 None
    Bagged FDA using gCV Pruning bagFDAGCV Classification earth degree
    Bagged Flexible Discriminant Analysis bagFDA Classification earth, mda degree, nprune
    Bagged Logic Regression logicBag Classification, Regression logicFS nleaves, ntrees
    Bagged MARS bagEarth Classification, Regression earth nprune, degree
    Bagged MARS using gCV Pruning bagEarthGCV Classification, Regression earth degree
    Bagged Model bag Classification, Regression caret vars
    Bayesian Additive Regression Trees bartMachine Classification, Regression bartMachine num_trees, k, alpha, beta, nu
    Bayesian Generalized Linear Model bayesglm Classification, Regression arm None
    Bayesian Regularized Neural Networks brnn Regression brnn neurons
    Bayesian Ridge Regression bridge Regression monomvn None
    Bayesian Ridge Regression (Model Averaged) blassoAveraged Regression monomvn None
    Binary Discriminant Analysis binda Classification binda lambda.freqs
    Boosted Classification Trees ada Classification ada, plyr iter, maxdepth, nu
    Boosted Generalized Additive Model gamboost Classification, Regression mboost, plyr, import mstop, prune
    Boosted Generalized Linear Model glmboost Classification, Regression plyr, mboost mstop, prune
    Boosted Linear Model BstLm Classification, Regression bst, plyr mstop, nu
    Boosted Logistic Regression LogitBoost Classification caTools nIter
    Boosted Smoothing Spline bstSm Classification, Regression bst, plyr mstop, nu
    Boosted Tree blackboost Classification, Regression party, mboost, plyr, partykit mstop, maxdepth
    Boosted Tree bstTree Classification, Regression bst, plyr mstop, maxdepth, nu
    C4.5-like Trees J48 Classification RWeka C, M
    C5.0 C5.0 Classification C50, plyr trials, model, winnow
    CART rpart Classification, Regression rpart cp
    CART rpart1SE Classification, Regression rpart None
    CART rpart2 Classification, Regression rpart maxdepth
    CART or Ordinal Responses rpartScore Classification rpartScore, plyr cp, split, prune
    CHi-squared Automated Interaction Detection chaid Classification CHAID alpha2, alpha3, alpha4
    Conditional Inference Random Forest cforest Classification, Regression party mtry
    Conditional Inference Tree ctree Classification, Regression party mincriterion
    Conditional Inference Tree ctree2 Classification, Regression party maxdepth, mincriterion
    Continuation Ratio Model for Ordinal Data vglmContRatio Classification VGAM parallel, link
    Cost-Sensitive C5.0 C5.0Cost Classification C50, plyr trials, model, winnow, cost
    Cost-Sensitive CART rpartCost Classification rpart, plyr cp, Cost
    Cubist cubist Regression Cubist committees, neighbors
    Cumulative Probability Model for Ordinal Data vglmCumulative Classification VGAM parallel, link
    DeepBoost deepboost Classification deepboost num_iter, tree_depth, beta, lambda, loss_type
    Diagonal Discriminant Analysis dda Classification sparsediscrim model, shrinkage
    Distance Weighted Discrimination with Polynomial Kernel dwdPoly Classification kerndwd lambda, qval, degree, scale
    Distance Weighted Discrimination with Radial Basis Function Kernel dwdRadial Classification kernlab, kerndwd lambda, qval, sigma
    Dynamic Evolving Neural-Fuzzy Inference System DENFIS Regression frbs Dthr, max.iter
    Elasticnet enet Regression elasticnet fraction, lambda
    Ensembles of Generalized Linear Models randomGLM Classification, Regression randomGLM maxInteractionOrder
    eXtreme Gradient Boosting xgbDART Classification, Regression xgboost, plyr nrounds, max_depth, eta, gamma, subsample, colsample_bytree, rate_drop, skip_drop, min_child_weight
    eXtreme Gradient Boosting xgbLinear Classification, Regression xgboost nrounds, lambda, alpha, eta
    eXtreme Gradient Boosting xgbTree Classification, Regression xgboost, plyr nrounds, max_depth, eta, gamma, colsample_bytree, min_child_weight, subsample
    Extreme Learning Machine elm Classification, Regression elmNN nhid, actfun
    Factor-Based Linear Discriminant Analysis RFlda Classification HiDimDA q
    Flexible Discriminant Analysis fda Classification earth, mda degree, nprune
    Fuzzy Inference Rules by Descent Method FIR.DM Regression frbs num.labels, max.iter
    Fuzzy Rules Using Chi's Method FRBCS.CHI Classification frbs num.labels, type.mf
    Fuzzy Rules Using Genetic Cooperative-Competitive Learning and Pittsburgh FH.GBML Classification frbs max.num.rule, popu.size, max.gen
    Fuzzy Rules Using the Structural Learning Algorithm on Vague Environment SLAVE Classification frbs num.labels, max.iter, max.gen
    Fuzzy Rules via MOGUL GFS.FR.MOGUL Regression frbs max.gen, max.iter, max.tune
    Fuzzy Rules via Thrift GFS.THRIFT Regression frbs popu.size, num.labels, max.gen
    Fuzzy Rules with Weight Factor FRBCS.W Classification frbs num.labels, type.mf
    Gaussian Process gaussprLinear Classification, Regression kernlab None
    Gaussian Process with Polynomial Kernel gaussprPoly Classification, Regression kernlab degree, scale
    Gaussian Process with Radial Basis Function Kernel gaussprRadial Classification, Regression kernlab sigma
    Generalized Additive Model using LOESS gamLoess Classification, Regression gam span, degree
    Generalized Additive Model using Splines bam Classification, Regression mgcv select, method
    Generalized Additive Model using Splines gam Classification, Regression mgcv select, method
    Generalized Additive Model using Splines gamSpline Classification, Regression gam df
    Generalized Linear Model glm Classification, Regression None
    Generalized Linear Model with Stepwise Feature Selection glmStepAIC Classification, Regression MASS None
    Generalized Partial Least Squares gpls Classification gpls K.prov
    Genetic Lateral Tuning and Rule Selection of Linguistic Fuzzy Systems GFS.LT.RS Regression frbs popu.size, num.labels, max.gen
    glmnet glmnet Classification, Regression glmnet, Matrix alpha, lambda
    glmnet glmnet_h2o Classification, Regression h2o alpha, lambda
    Gradient Boosting Machines gbm_h2o Classification, Regression h2o ntrees, max_depth, min_rows, learn_rate, col_sample_rate
    Greedy Prototype Selection protoclass Classification proxy, protoclass eps, Minkowski
    Heteroscedastic Discriminant Analysis hda Classification hda gamma, lambda, newdim
    High Dimensional Discriminant Analysis hdda Classification HDclassif threshold, model
    High-Dimensional Regularized Discriminant Analysis hdrda Classification sparsediscrim gamma, lambda, shrinkage_type
    Hybrid Neural Fuzzy Inference System HYFIS Regression frbs num.labels, max.iter
    Independent Component Regression icr Regression fastICA n.comp
    k-Nearest Neighbors kknn Classification, Regression kknn kmax, distance, kernel
    k-Nearest Neighbors knn Classification, Regression k
    L2 Regularized Linear Support Vector Machines with Class Weights svmLinearWeights2 Classification LiblineaR cost, Loss, weight
    L2 Regularized Support Vector Machine (dual) with Linear Kernel svmLinear3 Classification, Regression LiblineaR cost, Loss
    Learning Vector Quantization lvq Classification class size, k
    Least Angle Regression lars Regression lars fraction
    Least Angle Regression lars2 Regression lars step
    Least Squares Support Vector Machine lssvmLinear Classification kernlab tau
    Least Squares Support Vector Machine with Polynomial Kernel lssvmPoly Classification kernlab degree, scale, tau
    Least Squares Support Vector Machine with Radial Basis Function Kernel lssvmRadial Classification kernlab sigma, tau
    Linear Discriminant Analysis lda Classification MASS None
    Linear Discriminant Analysis lda2 Classification MASS dimen
    Linear Discriminant Analysis with Stepwise Feature Selection stepLDA Classification klaR, MASS maxvar, direction
    Linear Distance Weighted Discrimination dwdLinear Classification kerndwd lambda, qval
    Linear Regression lm Regression intercept
    Linear Regression with Backwards Selection leapBackward Regression leaps nvmax
    Linear Regression with Forward Selection leapForward Regression leaps nvmax
    Linear Regression with Stepwise Selection leapSeq Regression leaps nvmax
    Linear Regression with Stepwise Selection lmStepAIC Regression MASS None
    Linear Support Vector Machines with Class Weights svmLinearWeights Classification e1071 cost, weight
    Localized Linear Discriminant Analysis loclda Classification klaR k
    Logic Regression logreg Classification, Regression LogicReg treesize, ntrees
    Logistic Model Trees LMT Classification RWeka iter
    Maximum Uncertainty Linear Discriminant Analysis Mlda Classification HiDimDA None
    Mixture Discriminant Analysis mda Classification mda subclasses
    Model Averaged Naive Bayes Classifier manb Classification bnclassify smooth, prior
    Model Averaged Neural Network avNNet Classification, Regression nnet size, decay, bag
    Model Rules M5Rules Regression RWeka pruned, smoothed
    Model Tree M5 Regression RWeka pruned, smoothed, rules
    Monotone Multi-Layer Perceptron Neural Network monmlp Classification, Regression monmlp hidden1, n.ensemble
    Multi-Layer Perceptron mlp Classification, Regression RSNNS size
    Multi-Layer Perceptron mlpWeightDecay Classification, Regression RSNNS size, decay
    Multi-Layer Perceptron, multiple layers mlpWeightDecayML Classification, Regression RSNNS layer1, layer2, layer3, decay
    Multi-Layer Perceptron, with multiple layers mlpML Classification, Regression RSNNS layer1, layer2, layer3
    Multi-Step Adaptive MCP-Net msaenet Classification, Regression msaenet alphas, nsteps, scale
    Multilayer Perceptron Network by Stochastic Gradient Descent mlpSGD Classification, Regression FCNN4R, plyr size, l2reg, lambda, learn_rate, momentum, gamma, minibatchsz, repeats
    Multilayer Perceptron Network with Dropout mlpKerasDropout Classification, Regression keras size, dropout, batch_size, lr, rho, decay, activation
    Multilayer Perceptron Network with Dropout mlpKerasDropoutCost Classification keras size, dropout, batch_size, lr, rho, decay, cost, activation
    Multilayer Perceptron Network with Weight Decay mlpKerasDecay Classification, Regression keras size, lambda, batch_size, lr, rho, decay, activation
    Multilayer Perceptron Network with Weight Decay mlpKerasDecayCost Classification keras size, lambda, batch_size, lr, rho, decay, cost, activation
    Multivariate Adaptive Regression Spline earth Classification, Regression earth nprune, degree
    Multivariate Adaptive Regression Splines gcvEarth Classification, Regression earth degree
    Naive Bayes naive_bayes Classification naivebayes laplace, usekernel, adjust
    Naive Bayes nb Classification klaR fL, usekernel, adjust
    Naive Bayes Classifier nbDiscrete Classification bnclassify smooth
    Naive Bayes Classifier with Attribute Weighting awnb Classification bnclassify smooth
    Nearest Shrunken Centroids pam Classification pamr threshold
    Negative Binomial Generalized Linear Model glm.nb Regression MASS link
    Neural Network mxnet Classification, Regression mxnet layer1, layer2, layer3, learning.rate, momentum, dropout, activation
    Neural Network mxnetAdam Classification, Regression mxnet layer1, layer2, layer3, dropout, beta1, beta2, learningrate, activation
    Neural Network neuralnet Regression neuralnet layer1, layer2, layer3
    Neural Network nnet Classification, Regression nnet size, decay
    Neural Networks with Feature Extraction pcaNNet Classification, Regression nnet size, decay
    Non-Convex Penalized Quantile Regression rqnc Regression rqPen lambda, penalty
    Non-Informative Model null Classification, Regression None
    Non-Negative Least Squares nnls Regression nnls None
    Oblique Random Forest ORFlog Classification obliqueRF mtry
    Oblique Random Forest ORFpls Classification obliqueRF mtry
    Oblique Random Forest ORFridge Classification obliqueRF mtry
    Oblique Random Forest ORFsvm Classification obliqueRF mtry
    Optimal Weighted Nearest Neighbor Classifier ownn Classification snn K
    Ordered Logistic or Probit Regression polr Classification MASS method
    Parallel Random Forest parRF Classification, Regression e1071, randomForest, foreach, import mtry
    partDSA partDSA Classification, Regression partDSA cut.off.growth, MPD
    Partial Least Squares kernelpls Classification, Regression pls ncomp
    Partial Least Squares pls Classification, Regression pls ncomp
    Partial Least Squares simpls Classification, Regression pls ncomp
    Partial Least Squares widekernelpls Classification, Regression pls ncomp
    Partial Least Squares Generalized Linear Models plsRglm Classification, Regression plsRglm nt, alpha.pvals.expli
    Patient Rule Induction Method PRIM Classification supervisedPRIM peel.alpha, paste.alpha, mass.min
    Penalized Discriminant Analysis pda Classification mda lambda
    Penalized Discriminant Analysis pda2 Classification mda df
    Penalized Linear Discriminant Analysis PenalizedLDA Classification penalizedLDA, plyr lambda, K
    Penalized Linear Regression penalized Regression penalized lambda1, lambda2
    Penalized Logistic Regression plr Classification stepPlr lambda, cp
    Penalized Multinomial Regression multinom Classification nnet decay
    Penalized Ordinal Regression ordinalNet Classification ordinalNet, plyr alpha, criteria, link
    Polynomial Kernel Regularized Least Squares krlsPoly Regression KRLS lambda, degree
    Principal Component Analysis pcr Regression pls ncomp
    Projection Pursuit Regression ppr Regression nterms
    Quadratic Discriminant Analysis qda Classification MASS None
    Quadratic Discriminant Analysis with Stepwise Feature Selection stepQDA Classification klaR, MASS maxvar, direction
    Quantile Random Forest qrf Regression quantregForest mtry
    Quantile Regression Neural Network qrnn Regression qrnn n.hidden, penalty, bag
    Quantile Regression with LASSO penalty rqlasso Regression rqPen lambda
    Radial Basis Function Kernel Regularized Least Squares krlsRadial Regression KRLS, kernlab lambda, sigma
    Radial Basis Function Network rbf Classification, Regression RSNNS size
    Radial Basis Function Network rbfDDA Classification, Regression RSNNS negativeThreshold
    Random Ferns rFerns Classification rFerns depth
    Random Forest ordinalRF Classification e1071, ranger, dplyr, ordinalForest nsets, ntreeperdiv, ntreefinal
    Random Forest ranger Classification, Regression e1071, ranger, dplyr mtry, splitrule, min.node.size
    Random Forest Rborist Classification, Regression Rborist predFixed, minNode
    Random Forest rf Classification, Regression randomForest mtry
    Random Forest by Randomization extraTrees Classification, Regression extraTrees mtry, numRandomCuts
    Random Forest Rule-Based Model rfRules Classification, Regression randomForest, inTrees, plyr mtry, maxdepth
    Regularized Discriminant Analysis rda Classification klaR gamma, lambda
    Regularized Linear Discriminant Analysis rlda Classification sparsediscrim estimator
    Regularized Logistic Regression regLogistic Classification LiblineaR cost, loss, epsilon
    Regularized Random Forest RRF Classification, Regression randomForest, RRF mtry, coefReg, coefImp
    Regularized Random Forest RRFglobal Classification, Regression RRF mtry, coefReg
    Relaxed Lasso relaxo Regression relaxo, plyr lambda, phi
    Relevance Vector Machines with Linear Kernel rvmLinear Regression kernlab None
    Relevance Vector Machines with Polynomial Kernel rvmPoly Regression kernlab scale, degree
    Relevance Vector Machines with Radial Basis Function Kernel rvmRadial Regression kernlab sigma
    Ridge Regression ridge Regression elasticnet lambda
    Ridge Regression with Variable Selection foba Regression foba k, lambda
    Robust Linear Discriminant Analysis Linda Classification rrcov None
    Robust Linear Model rlm Regression MASS intercept, psi
    Robust Mixture Discriminant Analysis rmda Classification robustDA K, model
    Robust Quadratic Discriminant Analysis QdaCov Classification rrcov None
    Robust Regularized Linear Discriminant Analysis rrlda Classification rrlda lambda, hp, penalty
    Robust SIMCA RSimca Classification rrcovHD None
    ROC-Based Classifier rocc Classification rocc xgenes
    Rotation Forest rotationForest Classification rotationForest K, L
    Rotation Forest rotationForestCp Classification rpart, plyr, rotationForest K, L, cp
    Rule-Based Classifier JRip Classification RWeka NumOpt, NumFolds, MinWeights
    Rule-Based Classifier PART Classification RWeka threshold, pruned
    Self-Organizing Maps xyf Classification, Regression kohonen xdim, ydim, user.weights, topo
    Semi-Naive Structure Learner Wrapper nbSearch Classification bnclassify k, epsilon, smooth, final_smooth, direction
    Shrinkage Discriminant Analysis sda Classification sda diagonal, lambda
    SIMCA CSimca Classification rrcov, rrcovHD None
    Simplified TSK Fuzzy Rules FS.HGD Regression frbs num.labels, max.iter
    Single C5.0 Ruleset C5.0Rules Classification C50 None
    Single C5.0 Tree C5.0Tree Classification C50 None
    Single Rule Classification OneR Classification RWeka None
    Sparse Distance Weighted Discrimination sdwd Classification sdwd lambda, lambda2
    Sparse Linear Discriminant Analysis sparseLDA Classification sparseLDA NumVars, lambda
    Sparse Mixture Discriminant Analysis smda Classification sparseLDA NumVars, lambda, R
    Sparse Partial Least Squares spls Classification, Regression spls K, eta, kappa
    Spike and Slab Regression spikeslab Regression spikeslab, plyr vars
    Stabilized Linear Discriminant Analysis slda Classification ipred None
    Stabilized Nearest Neighbor Classifier snn Classification snn lambda
    Stacked AutoEncoder Deep Neural Network dnn Classification, Regression deepnet layer1, layer2, layer3, hidden_dropout, visible_dropout
    Stochastic Gradient Boosting gbm Classification, Regression gbm, plyr n.trees, interaction.depth, shrinkage, n.minobsinnode
    Subtractive Clustering and Fuzzy c-Means Rules SBC Regression frbs r.a, eps.high, eps.low
    Supervised Principal Component Analysis superpc Regression superpc threshold, n.components
    Support Vector Machines with Boundrange String Kernel svmBoundrangeString Classification, Regression kernlab length, C
    Support Vector Machines with Class Weights svmRadialWeights Classification kernlab sigma, C, Weight
    Support Vector Machines with Exponential String Kernel svmExpoString Classification, Regression kernlab lambda, C
    Support Vector Machines with Linear Kernel svmLinear Classification, Regression kernlab C
    Support Vector Machines with Linear Kernel svmLinear2 Classification, Regression e1071 cost
    Support Vector Machines with Polynomial Kernel svmPoly Classification, Regression kernlab degree, scale, C
    Support Vector Machines with Radial Basis Function Kernel svmRadial Classification, Regression kernlab sigma, C
    Support Vector Machines with Radial Basis Function Kernel svmRadialCost Classification, Regression kernlab C
    Support Vector Machines with Radial Basis Function Kernel svmRadialSigma Classification, Regression kernlab sigma, C
    Support Vector Machines with Spectrum String Kernel svmSpectrumString Classification, Regression kernlab length, C
    The Bayesian lasso blasso Regression monomvn sparsity
    The lasso lasso Regression elasticnet fraction
    Tree Augmented Naive Bayes Classifier tan Classification bnclassify score, smooth
    Tree Augmented Naive Bayes Classifier Structure Learner Wrapper tanSearch Classification bnclassify k, epsilon, smooth, final_smooth, sp
    Tree Augmented Naive Bayes Classifier with Attribute Weighting awtan Classification bnclassify score, smooth
    Tree Models from Genetic Algorithms evtree Classification, Regression evtree alpha
    Tree-Based Ensembles nodeHarvest Classification, Regression nodeHarvest maxinter, mode
    Variational Bayesian Multinomial Probit Regression vbmpRadial Classification vbmp estimateTheta
    Wang and Mendel Fuzzy Rules WM Regression frbs num.labels, type.mf
    Weighted Subspace Random Forest wsrf Classification wsrf mtry

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