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 |
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.Resamples | Combine MachineShop Objects |
C50Model | C5.0 Decision Trees and Rule-Based Model |
calibration | Model Calibration |
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.Resamples | 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.ModelFrame | Model Tuning Grid Expansion |
expand_modelgrid.recipe | Model Tuning Grid Expansion |
expand_modelgrid.TunedModel | 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.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 |
Grid | Tuning Grid Control |
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 |
ModeledFrame | ModeledInput Classes |
ModeledInput | ModeledInput Classes |
ModeledInput.formula | ModeledInput Classes |
ModeledInput.matrix | ModeledInput Classes |
ModeledInput.MLModel | ModeledInput Classes |
ModeledInput.MLModelFunction | ModeledInput Classes |
ModeledInput.ModelFrame | ModeledInput Classes |
ModeledInput.recipe | ModeledInput Classes |
ModeledRecipe | ModeledInput Classes |
ModelFrame | ModelFrame Class |
ModelFrame.formula | ModelFrame Class |
ModelFrame.matrix | ModelFrame Class |
modelinfo | Display Model Information |
models | Models |
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 |
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.numeric | Model Performance Metrics |
performance.Resamples | Model Performance Metrics |
performance.Surv | Model Performance Metrics |
performance_curve | Model Performance Curves |
performance_curve.default | Model Performance Curves |
performance_curve.Resamples | 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.Resamples | Model Performance Plots |
plot.VarImp | Model Performance Plots |
PLSModel | Partial Least Squares Model |
PoissonVariate | Discrete Variate Constructors |
POLRModel | Ordered Logistic or Probit Regression Model |
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.ListOf | Print MachineShop Objects |
print.MLModel | Print MachineShop Objects |
print.ModeledInput | Print MachineShop Objects |
print.ModelFrame | Print MachineShop Objects |
print.Performance | Print MachineShop Objects |
print.PerformanceCurve | Print MachineShop Objects |
print.RecipeGrid | Print MachineShop Objects |
print.Resamples | Print MachineShop Objects |
print.SelectedInput | Print MachineShop Objects |
print.SurvMatrix | Print MachineShop Objects |
print.TrainStep | Print MachineShop Objects |
print.TunedInput | Print MachineShop Objects |
print.VarImp | 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.recipe | Resample Estimation of Model Performance |
response | Extract Response Variable |
response.MLModelFit | Extract Response Variable |
response.ModelFrame | Extract Response Variable |
response.recipe | Extract Response Variable |
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 | Performance Metrics |
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.recipe | Selected Model Inputs |
SelectedModel | Selected Model |
SelectedModelFrame | Selected Model Inputs |
SelectedModelRecipe | Selected Model Inputs |
sensitivity | Performance Metrics |
settings | MachineShop Settings |
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.Performance | Model Performance Summaries |
summary.PerformanceCurve | Model Performance Summaries |
summary.Resamples | 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 |
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 |
[.ModelFrame | Extract Elements of an Object |