Machine Learning Models and Tools


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Documentation for package ‘MachineShop’ version 1.5.0

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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