eval_tree: Print decision tree performance according to different...

In treeheatr: Heatmap-Integrated Decision Tree Visualizations

Description

Print decision tree performance according to different metrics.

Usage

eval_tree(
  dat,
  target_lab = colnames(dat)[1],
  task = c("classification", "regression"),
  metrics = NULL
)

Arguments

dat	Dataframe with truths (column 'target_lab') and estimates (column 'y_hat') of samples from original dataset.
target_lab	Name of the column in data that contains target/label information.
task	Character string indicating the type of problem, either 'classification' (categorical outcome) or 'regression' (continuous outcome).
metrics	A set of metric functions to evaluate decision tree, defaults to common metrics for classification/regression problems. Can be defined with 'yardstick::metric_set'.

Value

Character string of the decision tree evaluation.

Examples

eval_tree(compute_tree(penguins, target_lab = 'species')$dat)

treeheatr documentation built on Nov. 20, 2020, 1:07 a.m.