AdaBagModel             Bagging with Classification Trees
AdaBoostModel           Boosting with Classification Trees
BARTMachineModel        Bayesian Additive Regression Trees Model
BARTModel               Bayesian Additive Regression Trees Model
BlackBoostModel         Gradient Boosting with Regression Trees
C50Model                C5.0 Decision Trees and Rule-Based Model
CForestModel            Conditional Random Forest Model
CoxModel                Proportional Hazards Regression Model
DiscreteVariate         Discrete Variate Constructors
EarthModel              Multivariate Adaptive Regression Splines Model
FDAModel                Flexible and Penalized Discriminant Analysis
                        Models
GAMBoostModel           Gradient Boosting with Additive Models
GBMModel                Generalized Boosted Regression Model
GLMBoostModel           Gradient Boosting with Linear Models
GLMModel                Generalized Linear Model
GLMNetModel             GLM Lasso or Elasticnet Model
ICHomes                 Iowa City Home Sales Dataset
KNNModel                Weighted k-Nearest Neighbor Model
LARSModel               Least Angle Regression, Lasso and Infinitesimal
                        Forward Stagewise Models
LDAModel                Linear Discriminant Analysis Model
LMModel                 Linear Models
MDAModel                Mixture Discriminant Analysis Model
MLControl               Resampling Controls
MLMetric                MLMetric Class Constructor
MLModel                 MLModel and MLModelFunction Class Constructors
MachineShop-package     MachineShop: Machine Learning Models and Tools
ModelFrame              ModelFrame Class
ModelSpecification      Model Specification
NNetModel               Neural Network Model
NaiveBayesModel         Naive Bayes Classifier Model
PLSModel                Partial Least Squares Model
POLRModel               Ordered Logistic or Probit Regression Model
ParameterGrid           Tuning Parameters Grid
ParsnipModel            Parsnip Model
QDAModel                Quadratic Discriminant Analysis Model
RFSRCModel              Fast Random Forest (SRC) Model
RPartModel              Recursive Partitioning and Regression Tree
                        Models
RandomForestModel       Random Forest Model
RangerModel             Fast Random Forest Model
SVMModel                Support Vector Machine Models
SelectedInput           Selected Model Inputs
SelectedModel           Selected Model
StackedModel            Stacked Regression Model
SuperModel              Super Learner Model
SurvMatrix              SurvMatrix Class Constructors
SurvRegModel            Parametric Survival Model
TreeModel               Classification and Regression Tree Models
TunedInput              Tuned Model Inputs
TunedModel              Tuned Model
TuningGrid              Tuning Grid Control
XGBModel                Extreme Gradient Boosting Models
as.MLInput              Coerce to an MLInput
as.MLModel              Coerce to an MLModel
as.data.frame           Coerce to a Data Frame
calibration             Model Calibration
case_weights            Extract Case Weights
combine                 Combine MachineShop Objects
confusion               Confusion Matrix
dependence              Partial Dependence
diff                    Model Performance Differences
expand_model            Model Expansion Over Tuning Parameters
expand_modelgrid        Model Tuning Grid Expansion
expand_params           Model Parameters Expansion
expand_steps            Recipe Step Parameters Expansion
extract                 Extract Elements of an Object
fit                     Model Fitting
inputs                  Model Inputs
lift                    Model Lift Curves
metricinfo              Display Performance Metric Information
metrics                 Performance Metrics
modelinfo               Display Model Information
models                  Models
performance             Model Performance Metrics
performance_curve       Model Performance Curves
plot                    Model Performance Plots
predict                 Model Prediction
print                   Print MachineShop Objects
quote                   Quote Operator
recipe_roles            Set Recipe Roles
resample                Resample Estimation of Model Performance
response                Extract Response Variable
rfe                     Recursive Feature Elimination
set_monitor             Training Parameters Monitoring Control
set_optim               Tuning Parameter Optimization
set_predict             Resampling Prediction Control
set_strata              Resampling Stratification Control
settings                MachineShop Settings
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
t.test                  Paired t-Tests for Model Comparisons
unMLModelFit            Revert an MLModelFit Object
varimp                  Variable Importance
