model_diagnostics: Dataset Level Model Diagnostics

In DALEX: moDel Agnostic Language for Exploration and eXplanation

Dataset Level Model Diagnostics

Description

This function performs model diagnostic of residuals. Residuals are calculated and plotted against predictions, true y values or selected variables. Find information how to use this function here: https://ema.drwhy.ai/residualDiagnostic.html.

Usage

model_diagnostics(explainer, variables = NULL, ...)

Arguments

explainer	a model to be explained, preprocessed by the explain function
variables	character - name of variables to be explained. Default NULL stands for all variables
...	other parameters

Value

An object of the class model_diagnostics. It's a data frame with residuals and selected variables.

References

Explanatory Model Analysis. Explore, Explain and Examine Predictive Models. https://ema.drwhy.ai/

Examples

library(DALEX)
apartments_lm_model <- lm(m2.price ~ ., data = apartments)
explainer_lm <- explain(apartments_lm_model,
                         data = apartments,
                         y = apartments$m2.price)
diag_lm <- model_diagnostics(explainer_lm)
diag_lm
plot(diag_lm)

library("ranger")
apartments_ranger_model <- ranger(m2.price ~ ., data = apartments)
explainer_ranger <- explain(apartments_ranger_model,
                         data = apartments,
                         y = apartments$m2.price)
diag_ranger <- model_diagnostics(explainer_ranger)
diag_ranger
plot(diag_ranger)
plot(diag_ranger, diag_lm)
plot(diag_ranger, diag_lm, variable = "y")
plot(diag_ranger, diag_lm, variable = "construction.year")
plot(diag_ranger, variable = "y", yvariable = "y_hat")
plot(diag_ranger, variable = "y", yvariable = "abs_residuals")
plot(diag_ranger, variable = "ids")

DALEX documentation built on Jan. 16, 2023, 1:06 a.m.