Man pages for brian-j-smith/MachineShop
Machine Learning Models and Tools

AdaBagModelBagging with Classification Trees
AdaBoostModelBoosting with Classification Trees
as.MLModelCoerce to an MLModel
BARTMachineModelBayesian Additive Regression Trees Model
BARTModelBayesian Additive Regression Trees Model
BlackBoostModelGradient Boosting with Regression Trees
C50ModelC5.0 Decision Trees and Rule-Based Model
calibrationModel Calibration
CForestModelConditional Random Forest Model
confusionConfusion Matrix
CoxModelProportional Hazards Regression Model
dependencePartial Dependence
deprecatedDeprecated Functions
diff-methodsModel Performance Differences
dot-Quote Operator
EarthModelMultivariate Adaptive Regression Splines Model
expand_modelModel Expansion Over Tuning Parameters
expand_paramsModel Parameters Expansion
expand_stepsRecipe Step Parameters Expansion
extract-methodsExtract Parts of an Object
FDAModelFlexible and Penalized Discriminant Analysis Models
fit-methodsModel Fitting
GAMBoostModelGradient Boosting with Additive Models
GBMModelGeneralized Boosted Regression Model
GLMBoostModelGradient Boosting with Linear Models
GLMModelGeneralized Linear Model
GLMNetModelGLM Lasso or Elasticnet Model
GridTuning Grid Control
ICHomesIowa City Home Sales Dataset
KNNModelWeighted k-Nearest Neighbor Model
LARSModelLeast Angle Regression, Lasso and Infinitesimal Forward...
LDAModelLinear Discriminant Analysis Model
liftModel Lift
LMModelLinear Models
MachineShop-packageMachineShop: Machine Learning Models and Tools
MDAModelMixture Discriminant Analysis Model
metricinfoDisplay Performance Metric Information
metricsPerformance Metrics
MLControlResampling Controls
MLMetricMLMetric Class Constructor
MLModelMLModel Class Constructor
ModelFrame-methodsModelFrame Class
modelinfoDisplay Model Information
modelsModel Functions
NaiveBayesModelNaive Bayes Classifier Model
NNetModelNeural Network Model
performanceModel Performance Metrics
performance_curvePerformance Curves
plot-methodsModel Performance Plots
PLSModelPartial Least Squares Model
POLRModelOrdered Logistic or Probit Regression Model
predictModel Prediction
print-methodsPrint MachineShop Objects
QDAModelQuadratic Discriminant Analysis Model
RandomForestModelRandom Forest Model
RangerModelFast Random Forest Model
resample-methodsResample Estimation of Model Performance
response-methodsExtract Response Variable
RPartModelRecursive Partitioning and Regression Tree Models
SelectedModelSelected Model
SelectedRecipeSelected Recipe
settingsMachineShop Settings
StackedModelStacked Regression Model
summary-methodsModel Performance Summary
SuperModelSuper Learner Model
SurvMatrixSurvMatrix Class Constructor
SurvRegModelParametric Survival Model
SVMModelSupport Vector Machine Models
TreeModelClassification and Regression Tree Models
t.testPaired t-Tests for Model Comparisons
TunedModelTuned Model
TunedRecipeTuned Recipe
varimpVariable Importance
XGBModelExtreme Gradient Boosting Models
brian-j-smith/MachineShop documentation built on Nov. 7, 2019, 10:09 p.m.