eval_tree {treeheatr}

Print decision tree performance according to different metrics.

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)