Description Usage Arguments Value Examples
View source: R/plot_what_if_2d.R
Function 'plot.what_if_2d_explainer' plots What-If Plots for a single prediction / observation.
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x |
a ceteris paribus explainer produced with the 'what_if_2d' function |
... |
currently will be ignored |
split_ncol |
number of columns for the 'facet_wrap' |
add_raster |
if TRUE then 'geom_raster' will be added to present levels with diverging colors |
add_contour |
if TRUE then 'geom_contour' will be added to present contours |
add_observation |
if TRUE then 'geom_point' will be added to present observation that is explained |
bins |
number of contours to be added |
a ggplot2 object
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | library("DALEX")
## Not run:
library("randomForest")
set.seed(59)
apartments_rf_model <- randomForest(m2.price ~ construction.year + surface + floor +
no.rooms + district, data = apartments)
explainer_rf <- explain(apartments_rf_model,
data = apartmentsTest[,2:6], y = apartmentsTest$m2.price)
new_apartment <- apartmentsTest[1, ]
new_apartment
wi_rf_2d <- what_if_2d(explainer_rf, observation = new_apartment)
wi_rf_2d
plot(wi_rf_2d)
plot(wi_rf_2d, add_contour = FALSE)
plot(wi_rf_2d, add_observation = FALSE)
plot(wi_rf_2d, add_raster = FALSE)
# HR data
model <- randomForest(status ~ gender + age + hours + evaluation + salary, data = HR)
pred1 <- function(m, x) predict(m, x, type = "prob")[,1]
explainer_rf_fired <- explain(model, data = HR[,1:5],
y = HR$status == "fired",
predict_function = pred1, label = "fired")
new_emp <- HR[1, ]
new_emp
wi_rf_2d <- what_if_2d(explainer_rf_fired, observation = new_emp)
wi_rf_2d
plot(wi_rf_2d)
## End(Not run)
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