print.individual_variable_effect {shapper} | R Documentation |
Print Individual Variable Effects
Description
Print Individual Variable Effects
Usage
## S3 method for class 'individual_variable_effect'
print(x, ...)
Arguments
x |
an individual variable importance explainer created with the |
... |
further arguments passed to or from other methods. |
Examples
have_shap <- reticulate::py_module_available("shap")
if(have_shap){
library("shapper")
library("DALEX")
library("randomForest")
Y_train <- HR$status
x_train <- HR[ , -6]
set.seed(123)
model_rf <- randomForest(x = x_train, y = Y_train, ntree= 50)
p_function <- function(model, data) predict(model, newdata = data, type = "prob")
ive_rf <- individual_variable_effect(model_rf, data = x_train, predict_function = p_function,
new_observation = x_train[1:2,], nsamples = 50)
print(ive_rf)
}else{
print('Python testing environment is required.')
}
[Package shapper version 0.1.3 Index]