asymmetric_cost_explorer {fastLogisticRegressionWrap}

Asymmetric Cost Explorer

Description

Given a set of desired proportions of predicted outcomes, what is the error rate for each of those models?

Usage

asymmetric_cost_explorer(
  phat,
  ybin,
  steps = seq(from = 0.001, to = 0.999, by = 0.001),
  outcome_of_analysis = 0,
  proportions_desired = seq(from = 0.1, to = 0.9, by = 0.1),
  proportion_tolerance = 0.01
)

Arguments

phat

The vector of probability estimates to be thresholded to make a binary decision

ybin

The true binary responses

steps

All possibile thresholds which must be a vector of numbers in (0, 1). Default is seq(from = 0.001, to = 0.999, by = 0.001).

outcome_of_analysis

Which class do you care about performance? Either 0 or 1 for the negative class or positive class. Default is 0.

proportions_desired

Which proportions of outcome_of_analysis class do you wish to understand performance for?

proportion_tolerance

If the model cannot match the proportion_desired within this amount, it does not return that model's performance. Default is 0.01.

Value

A table with column 1: proportions_desired, column 2: actual proportions (as close as possible), column 3: error rate, column 4: probability threshold.

Author(s)

Adam Kapelner