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.MLModel | Coerce to an MLModel |
| as.MLModel.MLModelFit | Coerce to an MLModel |
| as.MLModel.ModeledInput | 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.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 |
| deprecated | Deprecated Functions |
| 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 Class Constructor |
| MLModelFunction | Models |
| ModeledInput | Deprecated Functions |
| 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.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 |
| rpp | Deprecated Functions |
| 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 |