plot.fairness_pca {fairmodels} | R Documentation |
Plot fairness PCA
Description
Plot pca calculated on fairness_object metrics. Similar models and metrics should be close to each other. Plot doesn't work on multiple fairness_pca
objects.
Unlike in other plots here other fairness_pca
objects cannot be added.
Usage
## S3 method for class 'fairness_pca'
plot(x, scale = 0.5, ...)
Arguments
x |
|
scale |
scaling loadings plot, from 0 to 1 |
... |
other plot parameters |
Value
ggplot2
object
Examples
data("german")
y_numeric <- as.numeric(german$Risk) - 1
lm_model <- glm(Risk ~ .,
data = german,
family = binomial(link = "logit")
)
rf_model <- ranger::ranger(Risk ~ .,
data = german,
probability = TRUE,
num.trees = 200,
num.threads = 1
)
explainer_lm <- DALEX::explain(lm_model, data = german[, -1], y = y_numeric)
explainer_rf <- DALEX::explain(rf_model, data = german[, -1], y = y_numeric)
fobject <- fairness_check(explainer_lm, explainer_rf,
protected = german$Sex,
privileged = "male"
)
# same explainers with different cutoffs for female
fobject <- fairness_check(explainer_lm, explainer_rf, fobject,
protected = german$Sex,
privileged = "male",
cutoff = list(female = 0.4),
label = c("lm_2", "rf_2")
)
fpca <- fairness_pca(fobject)
plot(fpca)
[Package fairmodels version 1.2.1 Index]