Machine Learning Models and Tools


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Documentation for package ‘MachineShop’ version 2.8.0

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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

-- A --

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

-- B --

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 --

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

-- D --

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

-- E --

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

-- F --

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

-- 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
inputs Model Inputs

-- 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 Curves
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
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

-- N --

NaiveBayesModel Naive Bayes Classifier Model
NegBinomialVariate Discrete Variate Constructors
NNetModel Neural Network Model
npv Performance Metrics

-- O --

OOBControl Resampling Controls

-- P --

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 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

-- Q --

QDAModel Quadratic Discriminant Analysis Model
quote Quote Operator

-- R --

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

-- S --

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 --

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

-- U --

unMLModelFit Revert an MLModelFit Object

-- 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 --

+-method Combine MachineShop Objects
. Quote Operator
[-method Extract Elements of an Object
[.BinomialVariate Extract Elements of an Object
[.ModelFrame Extract Elements of an Object