pr_curve: Precision–Recall (PR)

In nikitagusarov/performancer: Performance Metrics for Discrete Choice Analysis

Precision–Recall (PR)

Description

Get Precision–Recall (PR) curve construction.

Usage

pr_curve(y_real, y_predicted, threshold_range = c(0, 1), threshold_step = 0.01)

Arguments

y_real	Observed values to compare with in matrix format.
y_predicted	Predicte values (probabiblities by class).
threshold_range	Decision boundary threshold range. Defaults to 'c(0, 1)' for basic probabilistic classifier, but other values may be used.
threshold_step	Step to use over the boundary threshold range. Defaults to 0.01 for binary classification.
...	Other parameters passed to base plot function.

Value

matrix of PR curve coordinates for given probabilistic classifier output.

nikitagusarov/performancer documentation built on Jan. 12, 2023, 12:19 a.m.