# Machine Learning Models and Tools

## Documentation for package ‘MachineShop’ version 1.5.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

A B C D E F G I K L M N O P Q R S T V W X misc

MachineShop-package | MachineShop: Machine Learning Models and Tools

## -- A --

accuracy | Performance Metrics
AdaBagModel | Bagging with Classification Trees
AdaBoostModel | Boosting with Classification Trees
auc | Performance Metrics

## -- B --

BARTMachineModel | Bayesian Additive Regression Trees Model
BARTModel | Bayesian Additive Regression Trees Model
BlackBoostModel | Gradient Boosting with Regression Trees
BootControl | Resampling Controls
BootOptimismControl | Resampling Controls
brier | Performance Metrics

## -- C --

C50Model | C5.0 Decision Trees and Rule-Based Model
Calibration | Model Calibration
calibration | Model Calibration
CForestModel | Conditional Random Forest Model
cindex | Performance Metrics
Confusion | Confusion Matrix
confusion | Confusion Matrix
ConfusionMatrix | Confusion Matrix
CoxModel | Proportional Hazards Regression Model
CoxStepAICModel | Proportional Hazards Regression Model
cross_entropy | Performance Metrics
Curves | Performance Curves
CVControl | Resampling Controls

## -- D --

dependence | Partial Dependence
diff | Model Performance Differences
diff.MLModelTune | Model Performance Differences
diff.Performance | Model Performance Differences
diff.Resamples | Model Performance Differences

## -- E --

EarthModel | Multivariate Adaptive Regression Splines Model
expand.model | Model Expansion Over a Grid of Tuning Parameters
extract | Extract Parts of an Object

## -- F --

FDAModel | Flexible and Penalized Discriminant Analysis Models
fit | Model Fitting
fit.formula | Model Fitting
fit.matrix | Model Fitting
fit.ModelFrame | Model Fitting
fit.recipe | Model Fitting
fnr | Performance Metrics
fpr | Performance Metrics
f_score | Performance Metrics

## -- G --

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

## -- I --

ICHomes | Iowa City Home Sales Dataset

## -- K --

kappa2 | Performance Metrics
KNNModel | Weighted k-Nearest Neighbor Model

## -- L --

LARSModel | Least Angle Regression, Lasso and Infinitesimal Forward Stagewise Models
LDAModel | Linear Discriminant Analysis Model
Lift | Model Lift
lift | Model Lift
LMModel | Linear Models

## -- M --

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
ModelFrame | ModelFrame Class
ModelFrame.formula | ModelFrame Class
ModelFrame.matrix | ModelFrame Class
modelinfo | Display Model Information
models | Display Model Information
mse | Performance Metrics
msle | Performance Metrics

## -- N --

NaiveBayesModel | Naive Bayes Classifier Model
NNetModel | Neural Network Model
npv | Performance Metrics

## -- O --

OOBControl | Resampling Controls

## -- P --

PDAModel | Flexible and Penalized Discriminant Analysis Models
performance | Model Performance Metrics
performance.Confusion | 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 | Performance Curves
performance_curve.default | Performance Curves
performance_curve.Resamples | Performance Curves
plot | Model Performance Plots
plot.Calibration | Model Performance Plots
plot.Confusion | Model Performance Plots
plot.ConfusionMatrix | Model Performance Plots
plot.Curves | Model Performance Plots
plot.Lift | Model Performance Plots
plot.MLModelTune | Model Performance Plots
plot.PartialDependence | Model Performance Plots
plot.Performance | Model Performance Plots
plot.Resamples | Model Performance Plots
plot.VarImp | Model Performance Plots
PLSModel | Partial Least Squares Model
POLRModel | Ordered Logistic or Probit Regression Model
ppv | Performance Metrics
precision | Performance Metrics
predict | Model Prediction
predict.MLModelFit | Model Prediction
pr_auc | Performance Metrics

## -- Q --

QDAModel | Quadratic Discriminant Analysis Model

## -- R --

r2 | Performance Metrics
RandomForestModel | Random Forest Model
RangerModel | Fast Random Forest Model
recall | Performance Metrics
resample | Resample Estimation of Model Performance
resample.formula | Resample Estimation of Model Performance
resample.matrix | Resample Estimation of Model Performance
resample.ModelFrame | Resample Estimation of Model Performance
resample.recipe | Resample Estimation of Model Performance
Resamples | Resample Estimation of Model Performance
response | Extract Response Variable
response.MLModelFit | Extract Response Variable
response.ModelFrame | Extract Response Variable
response.recipe | Extract Response Variable
rmse | Performance Metrics
rmsle | Performance Metrics
roc_auc | Performance Metrics
roc_index | Performance Metrics
RPartModel | Recursive Partitioning and Regression Tree Models
rpp | Performance Metrics

## -- S --

SelectedModel | Selected Model
sensitivity | Performance Metrics
specificity | Performance Metrics
SplitControl | Resampling Controls
StackedModel | Stacked Regression Model
summary | Model Performance Summary
summary.Confusion | Model Performance Summary
summary.ConfusionMatrix | Model Performance Summary
summary.Curves | Model Performance Summary
summary.MLModelTune | Model Performance Summary
summary.Performance | Model Performance Summary
summary.Resamples | Model Performance Summary
SuperModel | Super Learner Model
SurvEvents | SurvMatrix Class Constructor
SurvMatrix | SurvMatrix Class Constructor
SurvProbs | SurvMatrix Class Constructor
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 --

t.test | Paired t-Tests for Model Comparisons
t.test.PerformanceDiff | Paired t-Tests for Model Comparisons
tnr | Performance Metrics
tpr | Performance Metrics
TrainControl | Resampling Controls
TreeModel | Classification and Regression Tree Models
tune | Model Tuning and Selection
tune.formula | Model Tuning and Selection
tune.matrix | Model Tuning and Selection
tune.ModelFrame | Model Tuning and Selection
tune.recipe | Model Tuning and Selection
TunedModel | Tuned Model

## -- V --

varimp | Variable Importance

## -- W --

weighted_kappa2 | Performance Metrics

## -- X --

XGBDARTModel | Extreme Gradient Boosting Models
XGBLinearModel | Extreme Gradient Boosting Models
XGBModel | Extreme Gradient Boosting Models
XGBTreeModel | Extreme Gradient Boosting Models

## -- misc --

. | Quote Operator
[-method | Extract Parts of an Object
[.SurvMatrix | Extract Parts of an Object