View source: R/show_profiles.R
show_profiles | R Documentation |
Function show_profiles
adds a layer to a plot created with
plot.ceteris_paribus_explainer
.
show_profiles( x, ..., size = 0.5, alpha = 1, color = "#371ea3", variables = NULL )
x |
a ceteris paribus explainer produced with function |
... |
other explainers that shall be plotted together |
size |
a numeric. Size of lines to be plotted |
alpha |
a numeric between |
color |
a character. Either name of a color or name of a variable that should be used for coloring |
variables |
if not |
a ggplot2
layer
Explanatory Model Analysis. Explore, Explain, and Examine Predictive Models. https://ema.drwhy.ai/
library("DALEX") library("ingredients") selected_passangers <- select_sample(titanic_imputed, n = 100) selected_john <- titanic_imputed[1,] model_titanic_glm <- glm(survived ~ gender + age + fare, data = titanic_imputed, family = "binomial") explain_titanic_glm <- explain(model_titanic_glm, data = titanic_imputed[,-8], y = titanic_imputed[,8], label = "glm", verbose = FALSE) cp_rf <- ceteris_paribus(explain_titanic_glm, selected_passangers) cp_rf_john <- ceteris_paribus(explain_titanic_glm, selected_john) plot(cp_rf, variables = "age") + show_profiles(cp_rf_john, variables = "age", size = 2) library("ranger") model_titanic_rf <- ranger(survived ~., data = titanic_imputed, probability = TRUE) explain_titanic_rf <- explain(model_titanic_rf, data = titanic_imputed[,-8], y = titanic_imputed[,8], label = "ranger forest", verbose = FALSE) cp_rf <- ceteris_paribus(explain_titanic_rf, selected_passangers) cp_rf_john <- ceteris_paribus(explain_titanic_rf, selected_john) cp_rf pdp_rf <- aggregate_profiles(cp_rf, variables = "age") head(pdp_rf) plot(cp_rf, variables = "age") + show_observations(cp_rf, variables = "age") + show_rugs(cp_rf, variables = "age", color = "red") + show_profiles(cp_rf_john, variables = "age", color = "red", size = 2)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.