A B C D E F G I K L M N O P Q R S T U V W X misc
| MachineShop-package | MachineShop: Machine Learning Models and Tools | 
| accuracy | Performance Metrics | 
| AdaBagModel | Bagging with Classification Trees | 
| AdaBoostModel | Boosting with Classification Trees | 
| as.data.frame | Coerce to a Data Frame | 
| as.data.frame.ModelFrame | Coerce to a Data Frame | 
| as.data.frame.Resample | Coerce to a Data Frame | 
| as.data.frame.TabularArray | Coerce to a Data Frame | 
| as.MLInput | Coerce to an MLInput | 
| as.MLInput.MLModelFit | Coerce to an MLInput | 
| as.MLInput.ModelSpecification | Coerce to an MLInput | 
| as.MLModel | Coerce to an MLModel | 
| as.MLModel.MLModelFit | Coerce to an MLModel | 
| as.MLModel.ModelSpecification | Coerce to an MLModel | 
| as.MLModel.model_spec | Coerce to an MLModel | 
| auc | Performance Metrics | 
| BARTMachineModel | Bayesian Additive Regression Trees Model | 
| BARTModel | Bayesian Additive Regression Trees Model | 
| BinomialVariate | Discrete Variate Constructors | 
| BlackBoostModel | Gradient Boosting with Regression Trees | 
| BootControl | Resampling Controls | 
| BootOptimismControl | Resampling Controls | 
| brier | Performance Metrics | 
| c | Combine MachineShop Objects | 
| c.Calibration | Combine MachineShop Objects | 
| c.ConfusionList | Combine MachineShop Objects | 
| c.ConfusionMatrix | Combine MachineShop Objects | 
| c.LiftCurve | Combine MachineShop Objects | 
| c.ListOf | Combine MachineShop Objects | 
| c.PerformanceCurve | Combine MachineShop Objects | 
| c.Resample | Combine MachineShop Objects | 
| C50Model | C5.0 Decision Trees and Rule-Based Model | 
| calibration | Model Calibration | 
| case_weights | Extract Case Weights | 
| CForestModel | Conditional Random Forest Model | 
| cindex | Performance Metrics | 
| combine | Combine MachineShop Objects | 
| confusion | Confusion Matrix | 
| ConfusionMatrix | Confusion Matrix | 
| controls | Resampling Controls | 
| CoxModel | Proportional Hazards Regression Model | 
| CoxStepAICModel | Proportional Hazards Regression Model | 
| cross_entropy | Performance Metrics | 
| curves | Model Performance Curves | 
| CVControl | Resampling Controls | 
| CVOptimismControl | Resampling Controls | 
| dependence | Partial Dependence | 
| diff | Model Performance Differences | 
| diff.MLModel | Model Performance Differences | 
| diff.Performance | Model Performance Differences | 
| diff.Resample | Model Performance Differences | 
| DiscreteVariate | Discrete Variate Constructors | 
| EarthModel | Multivariate Adaptive Regression Splines Model | 
| expand_model | Model Expansion Over Tuning Parameters | 
| expand_modelgrid | Model Tuning Grid Expansion | 
| expand_modelgrid.formula | Model Tuning Grid Expansion | 
| expand_modelgrid.matrix | Model Tuning Grid Expansion | 
| expand_modelgrid.MLModel | Model Tuning Grid Expansion | 
| expand_modelgrid.MLModelFunction | Model Tuning Grid Expansion | 
| expand_modelgrid.ModelFrame | Model Tuning Grid Expansion | 
| expand_modelgrid.ModelSpecification | Model Tuning Grid Expansion | 
| expand_modelgrid.recipe | Model Tuning Grid Expansion | 
| expand_params | Model Parameters Expansion | 
| expand_steps | Recipe Step Parameters Expansion | 
| extract | Extract Elements of an Object | 
| FDAModel | Flexible and Penalized Discriminant Analysis Models | 
| fit | Model Fitting | 
| fit.formula | Model Fitting | 
| fit.matrix | Model Fitting | 
| fit.MLModel | Model Fitting | 
| fit.MLModelFunction | Model Fitting | 
| fit.ModelFrame | Model Fitting | 
| fit.ModelSpecification | Model Fitting | 
| fit.recipe | Model Fitting | 
| fnr | Performance Metrics | 
| fpr | Performance Metrics | 
| f_score | Performance Metrics | 
| GAMBoostModel | Gradient Boosting with Additive Models | 
| GBMModel | Generalized Boosted Regression Model | 
| gini | Performance Metrics | 
| GLMBoostModel | Gradient Boosting with Linear Models | 
| GLMModel | Generalized Linear Model | 
| GLMNetModel | GLM Lasso or Elasticnet Model | 
| GLMStepAICModel | Generalized Linear Model | 
| ICHomes | Iowa City Home Sales Dataset | 
| inputs | Model Inputs | 
| kappa2 | Performance Metrics | 
| KNNModel | Weighted k-Nearest Neighbor Model | 
| LARSModel | Least Angle Regression, Lasso and Infinitesimal Forward Stagewise Models | 
| LDAModel | Linear Discriminant Analysis Model | 
| lift | Model Lift Curves | 
| LMModel | Linear Models | 
| MachineShop | MachineShop: Machine Learning Models and Tools | 
| mae | Performance Metrics | 
| MDAModel | Mixture Discriminant Analysis Model | 
| metricinfo | Display Performance Metric Information | 
| metrics | Performance Metrics | 
| MLControl | Resampling Controls | 
| MLMetric | MLMetric Class Constructor | 
| MLMetric<- | MLMetric Class Constructor | 
| MLModel | MLModel and MLModelFunction Class Constructors | 
| MLModelFunction | MLModel and MLModelFunction Class Constructors | 
| ModelFrame | ModelFrame Class | 
| ModelFrame.formula | ModelFrame Class | 
| ModelFrame.matrix | ModelFrame Class | 
| modelinfo | Display Model Information | 
| models | Models | 
| ModelSpecification | Model Specification | 
| ModelSpecification.default | Model Specification | 
| ModelSpecification.formula | Model Specification | 
| ModelSpecification.matrix | Model Specification | 
| ModelSpecification.ModelFrame | Model Specification | 
| ModelSpecification.recipe | Model Specification | 
| mse | Performance Metrics | 
| msle | Performance Metrics | 
| NaiveBayesModel | Naive Bayes Classifier Model | 
| NegBinomialVariate | Discrete Variate Constructors | 
| NNetModel | Neural Network Model | 
| npv | Performance Metrics | 
| OOBControl | Resampling Controls | 
| ParameterGrid | Tuning Parameters Grid | 
| ParameterGrid.list | Tuning Parameters Grid | 
| ParameterGrid.param | Tuning Parameters Grid | 
| ParameterGrid.parameters | Tuning Parameters Grid | 
| ParsnipModel | Parsnip Model | 
| PDAModel | Flexible and Penalized Discriminant Analysis Models | 
| performance | Model Performance Metrics | 
| performance.BinomialVariate | Model Performance Metrics | 
| performance.ConfusionList | Model Performance Metrics | 
| performance.ConfusionMatrix | Model Performance Metrics | 
| performance.factor | Model Performance Metrics | 
| performance.matrix | Model Performance Metrics | 
| performance.MLModel | Model Performance Metrics | 
| performance.numeric | Model Performance Metrics | 
| performance.Resample | Model Performance Metrics | 
| performance.Surv | Model Performance Metrics | 
| performance.TrainingStep | Model Performance Metrics | 
| performance_curve | Model Performance Curves | 
| performance_curve.default | Model Performance Curves | 
| performance_curve.Resample | Model Performance Curves | 
| plot | Model Performance Plots | 
| plot.Calibration | Model Performance Plots | 
| plot.ConfusionList | Model Performance Plots | 
| plot.ConfusionMatrix | Model Performance Plots | 
| plot.LiftCurve | Model Performance Plots | 
| plot.MLModel | Model Performance Plots | 
| plot.PartialDependence | Model Performance Plots | 
| plot.Performance | Model Performance Plots | 
| plot.PerformanceCurve | Model Performance Plots | 
| plot.Resample | Model Performance Plots | 
| plot.TrainingStep | Model Performance Plots | 
| plot.VariableImportance | Model Performance Plots | 
| PLSModel | Partial Least Squares Model | 
| PoissonVariate | Discrete Variate Constructors | 
| POLRModel | Ordered Logistic or Probit Regression Model | 
| ppr | Performance Metrics | 
| ppv | Performance Metrics | 
| precision | Performance Metrics | 
| predict | Model Prediction | 
| predict-method | Model Prediction | 
| predict.MLModelFit | Model Prediction | 
| Print MachineShop Objects | |
| print.BinomialVariate | Print MachineShop Objects | 
| print.Calibration | Print MachineShop Objects | 
| print.DiscreteVariate | Print MachineShop Objects | 
| print.ListOf | Print MachineShop Objects | 
| print.MLControl | Print MachineShop Objects | 
| print.MLMetric | Print MachineShop Objects | 
| print.MLModel | Print MachineShop Objects | 
| print.MLModelFunction | Print MachineShop Objects | 
| print.ModelFrame | Print MachineShop Objects | 
| print.ModelRecipe | Print MachineShop Objects | 
| print.ModelSpecification | Print MachineShop Objects | 
| print.Performance | Print MachineShop Objects | 
| print.PerformanceCurve | Print MachineShop Objects | 
| print.RecipeGrid | Print MachineShop Objects | 
| print.Resample | Print MachineShop Objects | 
| print.SurvMatrix | Print MachineShop Objects | 
| print.SurvTimes | Print MachineShop Objects | 
| print.TrainingStep | Print MachineShop Objects | 
| print.VariableImportance | Print MachineShop Objects | 
| pr_auc | Performance Metrics | 
| QDAModel | Quadratic Discriminant Analysis Model | 
| quote | Quote Operator | 
| r2 | Performance Metrics | 
| RandomForestModel | Random Forest Model | 
| RangerModel | Fast Random Forest Model | 
| recall | Performance Metrics | 
| recipe_roles | Set Recipe Roles | 
| resample | Resample Estimation of Model Performance | 
| resample.formula | Resample Estimation of Model Performance | 
| resample.matrix | Resample Estimation of Model Performance | 
| resample.MLModel | Resample Estimation of Model Performance | 
| resample.MLModelFunction | Resample Estimation of Model Performance | 
| resample.ModelFrame | Resample Estimation of Model Performance | 
| resample.ModelSpecification | Resample Estimation of Model Performance | 
| resample.recipe | Resample Estimation of Model Performance | 
| response | Extract Response Variable | 
| response.MLModelFit | Extract Response Variable | 
| response.ModelFrame | Extract Response Variable | 
| response.ModelSpecification | Extract Response Variable | 
| response.recipe | Extract Response Variable | 
| rfe | Recursive Feature Elimination | 
| rfe.formula | Recursive Feature Elimination | 
| rfe.matrix | Recursive Feature Elimination | 
| rfe.MLModel | Recursive Feature Elimination | 
| rfe.MLModelFunction | Recursive Feature Elimination | 
| rfe.ModelFrame | Recursive Feature Elimination | 
| rfe.ModelSpecification | Recursive Feature Elimination | 
| rfe.recipe | Recursive Feature Elimination | 
| RFSRCFastModel | Fast Random Forest (SRC) Model | 
| RFSRCModel | Fast Random Forest (SRC) Model | 
| rmse | Performance Metrics | 
| rmsle | Performance Metrics | 
| roc_auc | Performance Metrics | 
| roc_index | Performance Metrics | 
| role_binom | Set Recipe Roles | 
| role_case | Set Recipe Roles | 
| role_pred | Set Recipe Roles | 
| role_surv | Set Recipe Roles | 
| RPartModel | Recursive Partitioning and Regression Tree Models | 
| SelectedInput | Selected Model Inputs | 
| SelectedInput.formula | Selected Model Inputs | 
| SelectedInput.list | Selected Model Inputs | 
| SelectedInput.matrix | Selected Model Inputs | 
| SelectedInput.ModelFrame | Selected Model Inputs | 
| SelectedInput.ModelSpecification | Selected Model Inputs | 
| SelectedInput.recipe | Selected Model Inputs | 
| SelectedModel | Selected Model | 
| SelectedModel.default | Selected Model | 
| SelectedModel.list | Selected Model | 
| SelectedModel.ModelSpecification | Selected Model | 
| SelectedModelFrame | Selected Model Inputs | 
| SelectedModelRecipe | Selected Model Inputs | 
| SelectedModelSpecification | Selected Model Inputs | 
| sensitivity | Performance Metrics | 
| settings | MachineShop Settings | 
| set_monitor | Training Parameters Monitoring Control | 
| set_monitor.MLControl | Training Parameters Monitoring Control | 
| set_monitor.MLOptimization | Training Parameters Monitoring Control | 
| set_monitor.ModelSpecification | Training Parameters Monitoring Control | 
| set_optim | Tuning Parameter Optimization | 
| set_optim_bayes | Tuning Parameter Optimization | 
| set_optim_bayes.ModelSpecification | Tuning Parameter Optimization | 
| set_optim_bfgs | Tuning Parameter Optimization | 
| set_optim_bfgs.ModelSpecification | Tuning Parameter Optimization | 
| set_optim_grid | Tuning Parameter Optimization | 
| set_optim_grid.ModelSpecification | Tuning Parameter Optimization | 
| set_optim_grid.TrainingParams | Tuning Parameter Optimization | 
| set_optim_grid.TunedInput | Tuning Parameter Optimization | 
| set_optim_grid.TunedModel | Tuning Parameter Optimization | 
| set_optim_method | Tuning Parameter Optimization | 
| set_optim_method.ModelSpecification | Tuning Parameter Optimization | 
| set_optim_pso | Tuning Parameter Optimization | 
| set_optim_pso.ModelSpecification | Tuning Parameter Optimization | 
| set_optim_sann | Tuning Parameter Optimization | 
| set_optim_sann.ModelSpecification | Tuning Parameter Optimization | 
| set_predict | Resampling Prediction Control | 
| set_strata | Resampling Stratification Control | 
| specificity | Performance Metrics | 
| SplitControl | Resampling Controls | 
| StackedModel | Stacked Regression Model | 
| step_kmeans | K-Means Clustering Variable Reduction | 
| step_kmedoids | K-Medoids Clustering Variable Selection | 
| step_lincomp | Linear Components Variable Reduction | 
| step_sbf | Variable Selection by Filtering | 
| step_spca | Sparse Principal Components Analysis Variable Reduction | 
| summary | Model Performance Summaries | 
| summary.ConfusionList | Model Performance Summaries | 
| summary.ConfusionMatrix | Model Performance Summaries | 
| summary.MLModel | Model Performance Summaries | 
| summary.MLModelFit | Model Performance Summaries | 
| summary.Performance | Model Performance Summaries | 
| summary.PerformanceCurve | Model Performance Summaries | 
| summary.Resample | Model Performance Summaries | 
| summary.TrainingStep | Model Performance Summaries | 
| SuperModel | Super Learner Model | 
| SurvEvents | SurvMatrix Class Constructors | 
| SurvMatrix | SurvMatrix Class Constructors | 
| SurvProbs | SurvMatrix Class Constructors | 
| SurvRegModel | Parametric Survival Model | 
| SurvRegStepAICModel | Parametric Survival Model | 
| SVMANOVAModel | Support Vector Machine Models | 
| SVMBesselModel | Support Vector Machine Models | 
| SVMLaplaceModel | Support Vector Machine Models | 
| SVMLinearModel | Support Vector Machine Models | 
| SVMModel | Support Vector Machine Models | 
| SVMPolyModel | Support Vector Machine Models | 
| SVMRadialModel | Support Vector Machine Models | 
| SVMSplineModel | Support Vector Machine Models | 
| SVMTanhModel | Support Vector Machine Models | 
| t.test | Paired t-Tests for Model Comparisons | 
| t.test.PerformanceDiff | Paired t-Tests for Model Comparisons | 
| tidy.step_kmeans | K-Means Clustering Variable Reduction | 
| tidy.step_lincomp | Linear Components Variable Reduction | 
| tidy.step_sbf | Variable Selection by Filtering | 
| tnr | Performance Metrics | 
| tpr | Performance Metrics | 
| TrainControl | Resampling Controls | 
| TreeModel | Classification and Regression Tree Models | 
| tunable.step_kmeans | K-Means Clustering Variable Reduction | 
| tunable.step_kmedoids | K-Medoids Clustering Variable Selection | 
| tunable.step_lincomp | Linear Components Variable Reduction | 
| tunable.step_spca | Sparse Principal Components Analysis Variable Reduction | 
| TunedInput | Tuned Model Inputs | 
| TunedInput.recipe | Tuned Model Inputs | 
| TunedModel | Tuned Model | 
| TunedModelRecipe | Tuned Model Inputs | 
| TuningGrid | Tuning Grid Control | 
| unMLModelFit | Revert an MLModelFit Object | 
| varimp | Variable Importance | 
| weighted_kappa2 | Performance Metrics | 
| XGBDARTModel | Extreme Gradient Boosting Models | 
| XGBLinearModel | Extreme Gradient Boosting Models | 
| XGBModel | Extreme Gradient Boosting Models | 
| XGBTreeModel | Extreme Gradient Boosting Models | 
| +-method | Combine MachineShop Objects | 
| . | Quote Operator | 
| [-method | Extract Elements of an Object | 
| [.BinomialVariate | Extract Elements of an Object |