audit | R Documentation |
The audit()
function is deprecated, use explain
from the DALEX
package instead.
audit(
object,
data = NULL,
y = NULL,
predict.function = NULL,
residual.function = NULL,
label = NULL,
predict_function = NULL,
residual_function = NULL
)
object |
An object containing a model or object of class explainer (see |
data |
Data.frame or matrix - data that will be used by further validation functions. If not provided, will be extracted from the model. |
y |
Response vector that will be used by further validation functions. Some functions may require an integer vector containing binary labels with values 0,1. If not provided, will be extracted from the model. |
predict.function |
Function that takes two arguments: model and data. It should return a numeric vector with predictions. |
residual.function |
Function that takes three arguments: model, data and response vector. It should return a numeric vector with model residuals for given data. If not provided, response residuals ( |
label |
Character - the name of the model. By default it's extracted from the 'class' attribute of the model. |
predict_function |
Function that takes two arguments: model and data. It should return a numeric vector with predictions. |
residual_function |
Function that takes three arguments: model, data and response vector. It should return a numeric vector with model residuals for given data. If not provided, response residuals ( |
An object of class explainer
.
data(titanic_imputed, package = "DALEX")
model_glm <- glm(survived ~ ., family = binomial, data = titanic_imputed)
audit_glm <- audit(model_glm,
data = titanic_imputed,
y = titanic_imputed$survived)
p_fun <- function(model, data) { predict(model, data, response = "link") }
audit_glm_newpred <- audit(model_glm,
data = titanic_imputed,
y = titanic_imputed$survived,
predict.function = p_fun)
library(randomForest)
model_rf <- randomForest(Species ~ ., data=iris)
audit_rf <- audit(model_rf)
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