abind, cli (>= 3.1.0), dials (>= 0.0.4), foreach, ggplot2 (>=
3.3.0), kernlab, magrittr, Matrix, methods, nnet, party,
polspline, progress, recipes (>= 0.2.0), rlang, rsample (>=
0.1.0), Rsolnp, survival, tibble, utils
'classes.R' 'MLControl.R' 'MLInput.R' 'MLMetric.R' 'MLModel.R'
'MLOptimization.R' 'ML_AdaBagModel.R' 'ML_AdaBoostModel.R'
'ML_BARTMachineModel.R' 'ML_BARTModel.R' 'ML_BlackBoostModel.R'
'ML_C50Model.R' 'ML_CForestModel.R' 'ML_CoxModel.R'
'ML_EarthModel.R' 'ML_FDAModel.R' 'ML_GAMBoostModel.R'
'ML_GBMModel.R' 'ML_GLMBoostModel.R' 'ML_GLMModel.R'
'ML_GLMNetModel.R' 'ML_KNNModel.R' 'ML_LARSModel.R'
'ML_LDAModel.R' 'ML_LMModel.R' 'ML_MDAModel.R' 'ML_NNetModel.R'
'ML_NaiveBayesModel.R' 'ML_ParsnipModel.R' 'ML_PLSModel.R'
'ML_POLRModel.R' 'ML_QDAModel.R' 'ML_RFSRCModel.R'
'ML_RPartModel.R' 'ML_RandomForestModel.R' 'ML_RangerModel.R'
'ML_SVMModel.R' 'ML_StackedModel.R' 'ML_SuperModel.R'
'ML_SurvRegModel.R' 'ML_TreeModel.R' 'ML_XGBModel.R'
'MachineShop-package.R' 'ModelFrame.R' 'ModelRecipe.R'
'ModelSpecification.R' 'TrainedInputs.R' 'TrainedModels.R'
'TrainingParams.R' 'append.R' 'calibration.R' 'case_comps.R'
'coerce.R' 'combine.R' 'conditions.R' 'confusion.R' 'convert.R'
'data.R' 'dependence.R' 'diff.R' 'expand.R' 'extract.R' 'fit.R'
'grid.R' 'metricinfo.R' 'metrics.R' 'metrics_factor.R'
'metrics_numeric.R' 'modelinfo.R' 'models.R' 'performance.R'
'performance_curve.R' 'plot.R' 'predict.R' 'predictors.R'
'print.R' 'recipe_roles.R' 'reexports.R' 'resample.R'
'response.R' 'rfe.R' 'settings.R' 'step_kmeans.R'
'step_kmedoids.R' 'step_lincomp.R' 'step_sbf.R' 'step_spca.R'
'summary.R' 'survival.R' 'utils.R' 'varimp.R'

'classes.R' 'conditions.R' 'MachineShop-package.R'
'MLControl.R' 'MLInput.R' 'MLMetric.R' 'MLModel.R'
'MLOptimization.R' 'ML_AdaBagModel.R' 'ML_AdaBoostModel.R'
'ML_BARTMachineModel.R' 'ML_BARTModel.R' 'ML_BlackBoostModel.R'
'ML_C50Model.R' 'ML_CForestModel.R' 'ML_CoxModel.R'
'ML_EarthModel.R' 'ML_FDAModel.R' 'ML_GAMBoostModel.R'
'ML_GBMModel.R' 'ML_GLMBoostModel.R' 'ML_GLMModel.R'
'ML_GLMNetModel.R' 'ML_KNNModel.R' 'ML_LARSModel.R'
'ML_LDAModel.R' 'ML_LMModel.R' 'ML_MDAModel.R' 'ML_NNetModel.R'
'ML_NaiveBayesModel.R' 'ML_ParsnipModel.R' 'ML_PLSModel.R'
'ML_POLRModel.R' 'ML_QDAModel.R' 'ML_RFSRCModel.R'
'ML_RPartModel.R' 'ML_RandomForestModel.R' 'ML_RangerModel.R'
'ML_SVMModel.R' 'ML_StackedModel.R' 'ML_SuperModel.R'
'ML_SurvRegModel.R' 'ML_TreeModel.R' 'ML_XGBModel.R'
'ModelFrame.R' 'ModelRecipe.R' 'ModelSpecification.R'
'TrainedInputs.R' 'TrainedModels.R' 'TrainingParams.R'
'append.R' 'calibration.R' 'case_comps.R' 'coerce.R'
'combine.R' 'confusion.R' 'convert.R' 'data.R' 'dependence.R'
'diff.R' 'expand.R' 'extract.R' 'fit.R' 'grid.R' 'metricinfo.R'
'metrics.R' 'metrics_factor.R' 'metrics_numeric.R'
'modelinfo.R' 'models.R' 'performance.R' 'performance_curve.R'
'plot.R' 'predict.R' 'print.R' 'recipe_roles.R' 'reexports.R'
'resample.R' 'response.R' 'rfe.R' 'settings.R' 'step_kmeans.R'
'step_kmedoids.R' 'step_lincomp.R' 'step_sbf.R' 'step_spca.R'
'summary.R' 'survival.R' 'utils.R' 'varimp.R'