Prediction Models

Regression models (n=16)

• BGLM: Bayesian Generalized Linear Model, available in arm
• BLASSO: Bayesian Lasso, available in monomvn
• BRNN: Bayesian Regularized Neural Networks, available in brnn
• GBM: Stochastic Gradient Boosting, available in gbm and plyr
• GLM: Generalized Linear Model
• GLMNET: Lasso and Elastic-Net Regularized Generalized Linear Models, available in glmnet and Matrix
• GP-Poly: Gaussian Process with Polynomial Kernel, available in kernlab
• GP-Radial: Gaussian Process with Radial Kernel, available in kernlab
• KNN: k-Nearest Neighbors, available in kknn
• LASSO: Lasso Model, available in elasticnet
• MARS: Multivariate Adaptive Regression Spline, available in earth
• MLR: Multivariate Linear Regression
• RF: Random Forest, available in randomForest
• RIDGE: Ridge Regression, available in elasticnet
• SVM-Radial: Support Vector Machines with Radial Kernel, available in kernlab
• SVM-Linear: Support Vector Machines with Linear Kernel, available in e1071

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Classification models (n=16)

• CART: Classification And Regression Trees, available in rpart
• GBM: Stochastic Gradient Boosting, available in gbm and plyr
• GLMNET: Lasso and Elastic-Net Regularized Generalized Linear Models, available in glmnet and Matrix
• KNN: k-Nearest Neighbors, available in kknn
• LDA: Linear Discriminant Analysis, available in MASS
• LLDA: Localized Linear Discriminant Analysis, available in klaR
• MARS: Multivariate Adaptive Regression Spline, available in earth
• MDA: Mixture Discriminant Analysis, available in mda
• NBC: Naive Bayes, available in naivebayes
• NNET: Neural Network, available in nnet
• PDA: Penalized Discriminant Analysis, available in mda
• PLS: Partial Least Squares, available in pls
• RDA: Regularized Discriminant Analysis, available in klaR
• RF: Random Forest, available in randomForest
• SVM-Linear: Support Vector Machines with Linear Kernel, available in e1071
• SVM-Radial: Support Vector Machines with Radial Kernel, available in kernlab