PlotFairness {aihuman} | R Documentation |
Plot the principal fairness
Description
See Figure 5 for example.
Usage
PlotFairness(
res,
top.margin = 0.01,
y.max = 0.2,
y.min = -0.1,
r.labels = c("Safe", "Easily\nPreventable", "Preventable", "Risky"),
label = TRUE
)
Arguments
res |
The data frame generated from |
top.margin |
The index of subgroups (within the output of CalAPCE/CalAPCEparallel) that corresponds to the protected attributes. |
y.max |
Maximum value of y-axis. |
y.min |
Minimum value of y-axis. |
r.labels |
Label of each principal stratum. |
label |
A logical argument whether to specify label. |
Value
A data.frame
of the delta.
Examples
data(synth)
subgroup_synth = list(1:nrow(synth), which(synth$Sex==0), which(synth$Sex==1),
which(synth$Sex==1&synth$White==0), which(synth$Sex==1&synth$White==1))
sample_mcmc = AiEvalmcmc(data = synth, n.mcmc = 10)
sample_apce = CalAPCE(data = synth, mcmc.re = sample_mcmc, subgroup = subgroup_synth,
burnin = 0)
sample_fair = CalFairness(sample_apce)
PlotFairness(sample_fair, y.max = 0.4, y.min = -0.4, r.labels = c("Safe", "Preventable 1",
"Preventable 2", "Preventable 3", "Risky"))
[Package aihuman version 0.1.0 Index]