Multi-Target Automated Tree Engine (MuTATE)

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Documentation for package ‘MuTATE’ version 0.1.0

• DESCRIPTION file
• User guides, package vignettes and other documentation
• Package README

Help Pages

Cat_Eval	Evaluate features across multiple outcomes and outcome types
Cont_Eval	Evaluate features across multiple outcomes and outcome types
Count_Eval	Evaluate features across multiple outcomes and outcome types
CVsplitEval	Evaluate the performance of binary classifiers
CV_Tune	CV_Tune: Cross-Validated Hyperparameter Tuning for MTPart Models
MTPart	Construct multi-target decision trees
MTPartSummary	MTPartSummary Function
MTPrune	MTPrune: Prune a Decision Tree Using Minimal Cost-Complexity Pruning
MTSummary	Summarize multiple outcome variables
MTTest	MTTest: Test Multi-Target Tree
MultiEval	Evaluate features across multiple outcomes and outcome types
mutate_example	Synthetic example dataset for MuTATE
PlotTree	PlotTree: Plot Decision Tree
SplitPrep	Prepare data for splitting in a decision tree
Surv_Eval	Evaluate features across multiple outcomes and outcome types