remove DALEX from examples

ModelOriented · May 27, 2020 · 7acf1d4 · 7acf1d4
1 parent e95565b
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diff --git a/R/audit.R b/R/audit.R
@@ -18,7 +18,7 @@
 #' @importFrom stats model.frame sd
 #'
 #' @examples
-#' library(DALEX)
+#' data(titanic_imputed, package = "DALEX")
 #'
 #' model_glm <- glm(survived ~ ., family = binomial, data = titanic_imputed)
 #' audit_glm <- audit(model_glm,

diff --git a/R/check_residuals.R b/R/check_residuals.R
@@ -14,17 +14,15 @@
 #' @importFrom  utils head tail
 #'
 #' @examples
-#' library(DALEX)
 #' dragons <- DALEX::dragons[1:100, ]
 #' lm_model <- lm(life_length ~ ., data = dragons)
-#' lm_exp <- explain(lm_model, data = dragons, y = dragons$life_length)
-#' library(auditor)
-#' check_residuals(lm_exp)
+#' lm_audit <- audit(lm_model, data = dragons, y = dragons$life_length)
+#' check_residuals(lm_audit)
 #'  \dontrun{
 #'  library("randomForest")
 #'  rf_model <- randomForest(life_length ~ ., data = dragons)
-#'  rf_exp <- explain(rf_model, data = dragons, y = dragons$life_length)
-#'  check_residuals(rf_exp)
+#'  rf_audit <- audit(rf_model, data = dragons, y = dragons$life_length)
+#'  check_residuals(rf_audit)
 #' }
 check_residuals <- function(object, ...) {
   if(!("explainer" %in% class(object))) stop("The function requires an object created with explain() function from the DALEX package.")
@@ -47,14 +45,12 @@ check_residuals <- function(object, ...) {
 #' @export
 #'
 #' @examples
-#' library(DALEX)
 #' dragons <- DALEX::dragons[1:100, ]
 #' lm_model <- lm(life_length ~ ., data = dragons)
-#' library(auditor)
-#' lm_exp <- explain(lm_model, data = dragons, y = dragons$life_length)
-#' check_residuals_outliers(lm_exp)
+#' lm_audit <- audit(lm_model, data = dragons, y = dragons$life_length)
+#' check_residuals_outliers(lm_audit)
 check_residuals_outliers <- function(object, n = 5) {
-  if(!("explainer" %in% class(object))) stop("The function requires an object created with explain() function from the DALEX package.")
+  if(!("explainer" %in% class(object))) stop("The function requires an object created with audit() function.")
 
 
   model_name <- object$label
@@ -95,14 +91,12 @@ check_residuals_outliers <- function(object, n = 5) {
 #' @export
 #'
 #' @examples
-#' library(DALEX)
 #' dragons <- DALEX::dragons[1:100, ]
 #' lm_model <- lm(life_length ~ ., data = dragons)
-#' lm_exp <- explain(lm_model, data = dragons, y = dragons$life_length)
-#' library(auditor)
-#' check_residuals_autocorrelation(lm_exp)
+#' lm_audit <- audit(lm_model, data = dragons, y = dragons$life_length)
+#' check_residuals_autocorrelation(lm_audit)
 check_residuals_autocorrelation <- function(object, method = "pearson") {
-  if(!("explainer" %in% class(object))) stop("The function requires an object created with explain() function from the DALEX package.")
+  if(!("explainer" %in% class(object))) stop("The function requires an object created with audit().")
 
   model_name <- object$label
 

diff --git a/R/model_cooksdistance.R b/R/model_cooksdistance.R
@@ -10,19 +10,18 @@
 #' @return An object of the class \code{auditor_model_cooksdistance}.
 #'
 #' @examples
-#' library(DALEX)
+#' data(titanic_imputed, package = "DALEX")
 #'
 #' # fit a model
 #' model_glm <- glm(survived ~ ., family = binomial, data = titanic_imputed)
 #'
 #' # use DALEX package to wrap up a model into explainer
-#' exp_glm <- explain(model_glm,
+#' glm_audit <- audit(model_glm,
 #'                    data = titanic_imputed,
 #'                    y = titanic_imputed$survived)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' mc <- model_cooksdistance(exp_glm)
+#' mc <- model_cooksdistance(glm_audit)
 #' mc
 #'
 #' plot(mc)

diff --git a/R/model_evaluation.R b/R/model_evaluation.R
@@ -13,19 +13,17 @@
 #' @return An object of the class \code{auditor_model_evaluation}.
 #'
 #' @examples
-#' library(DALEX)
+#' data(titanic_imputed, package = "DALEX")
 #'
 #' # fit a model
 #' model_glm <- glm(survived ~ ., family = binomial, data = titanic_imputed)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_glm <- explain(model_glm,
+#' glm_audit <- audit(model_glm,
 #'                    data= titanic_imputed,
 #'                    y = titanic_imputed$survived)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' me <- model_evaluation(exp_glm)
+#' me <- model_evaluation(glm_audit)
 #' me
 #'
 #' plot(me)

diff --git a/R/model_halfnormal.R b/R/model_halfnormal.R
@@ -7,19 +7,17 @@
 #' @param ... other parameters passed do \code{\link[hnp]{hnp}} function.
 #'
 #' @examples
-#' library(DALEX)
+#' data(titanic_imputed, package = "DALEX")
 #'
 #' # fit a model
 #' model_glm <- glm(survived ~ ., family = binomial, data = titanic_imputed)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_glm <- explain(model_glm,
+#' glm_audit <- audit(model_glm,
 #'                    data = titanic_imputed,
 #'                    y = titanic_imputed$survived)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' mh <- model_halfnormal(exp_glm)
+#' mh <- model_halfnormal(glm_audit)
 #' mh
 #'
 #' plot(mh)

diff --git a/R/model_performance.R b/R/model_performance.R
@@ -26,19 +26,19 @@
 #' @return An object of the class \code{auditor_model_performance}.
 #'
 #' @examples
-#' library(DALEX)
+#' data(titanic_imputed, package = "DALEX")
 #'
 #' # fit a model
 #' model_glm <- glm(survived ~ ., family = binomial, data = titanic_imputed)
 #'
 #' # use DALEX package to wrap up a model into explainer
-#' exp_glm <- explain(model_glm,
+#' glm_audit <- audit(model_glm,
 #'                    data = titanic_imputed,
 #'                    y = titanic_imputed$survived)
 #'
 #' # validate a model with auditor
 #' library(auditor)
-#' mp <- model_performance(exp_glm)
+#' mp <- model_performance(glm_audit)
 #' mp
 #'
 #' plot(mp)

diff --git a/R/model_residual.R b/R/model_residual.R
@@ -19,14 +19,12 @@
 #' # fit a model
 #' model_glm <- glm(m2.price ~ ., data = apartments)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_glm <- explain(model_glm,
+#' glm_audit <- explain(model_glm,
 #'                    data = apartments,
 #'                    y = apartments$m2.price)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' mr <- model_residual(exp_glm)
+#' mr <- model_residual(glm_audit)
 #' mr
 #'
 #' plot(mr)

diff --git a/R/plot.R b/R/plot.R
@@ -32,26 +32,24 @@
 #' # fit a model
 #' model_lm <- lm(life_length ~ ., data = dragons)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_lm <- DALEX::explain(model_lm, data = dragons, y = dragons$life_length)
+#' lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' mr_lm <- model_residual(exp_lm)
+#' mr_lm <- model_residual(lm_audit)
 #'
 #' # plot results
 #' plot(mr_lm)
 #' plot(mr_lm, type = "prediction")
 #'
-#' hn_lm <- model_halfnormal(exp_lm)
+#' hn_lm <- model_halfnormal(lm_audit)
 #' plot(hn_lm)
 #'
 #' library(randomForest)
 #' model_rf <- randomForest(life_length~., data = dragons)
-#' exp_rf <- DALEX::explain(model_rf, data = dragons, y = dragons$life_length)
+#' rf_audit <- audit(model_rf, data = dragons, y = dragons$life_length)
 #'
-#' mp_rf <- model_performance(exp_rf)
-#' mp_lm <- model_performance(exp_lm)
+#' mp_rf <- model_performance(rf_audit)
+#' mp_lm <- model_performance(lm_audit)
 #' plot(mp_lm, mp_rf)
 #'
 #' @import ggplot2

diff --git a/R/plotD3.R b/R/plotD3.R
@@ -27,18 +27,16 @@
 #' # fit a model
 #' model_lm <- lm(life_length ~ ., data = dragons)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_lm <- DALEX::explain(model_lm, data = dragons, y = dragons$life_length)
+#' lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' mr_lm <- model_residual(exp_lm)
+#' mr_lm <- model_residual(lm_audit)
 #'
 #' # plot results
 #' plotD3(mr_lm)
 #' plotD3(mr_lm, type = "prediction")
 #'
-#' hn_lm <- model_halfnormal(exp_lm)
+#' hn_lm <- model_halfnormal(lm_audit)
 #' plotD3(hn_lm)
 #'
 #'

diff --git a/R/plotD3_acf.R b/R/plotD3_acf.R
@@ -21,20 +21,18 @@
 #' # fit a model
 #' model_lm <- lm(life_length ~ ., data = dragons)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_lm <- DALEX::explain(model_lm, data = dragons, y = dragons$life_length)
+#' lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' mr_lm <- model_residual(exp_lm)
+#' mr_lm <- model_residual(lm_audit)
 #'
 #' # plot results
 #' plotD3_acf(mr_lm)
 #'
 #' library(randomForest)
 #' model_rf <- randomForest(life_length~., data = dragons)
-#' exp_rf <- DALEX::explain(model_rf, data = dragons, y = dragons$life_length)
-#' mr_rf <- model_residual(exp_rf)
+#' rf_audit <- audit(model_rf, data = dragons, y = dragons$life_length)
+#' mr_rf <- model_residual(rf_audit)
 #' plotD3_acf(mr_lm, mr_rf)
 #'
 #' @importFrom stats qnorm acf

diff --git a/R/plotD3_autocorrelation.R b/R/plotD3_autocorrelation.R
@@ -25,12 +25,10 @@
 #' # fit a model
 #' model_lm <- lm(life_length ~ ., data = dragons)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_lm <- DALEX::explain(model_lm, data = dragons, y = dragons$life_length)
+#' lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' mr_lm <- model_residual(exp_lm)
+#' mr_lm <- model_residual(lm_audit)
 #'
 #' # plot results
 #' plotD3_autocorrelation(mr_lm)

diff --git a/R/plotD3_cooksdistance.R b/R/plotD3_cooksdistance.R
@@ -29,12 +29,10 @@
 #' # fit a model
 #' model_lm <- lm(life_length ~ ., data = dragons)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_lm <- DALEX::explain(model_lm, data = dragons, y = dragons$life_length)
+#' lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' cd_lm <- model_cooksdistance(exp_lm)
+#' cd_lm <- model_cooksdistance(lm_audit)
 #'
 #' # plot results
 #' plotD3_cooksdistance(cd_lm, nlabel = 5)

diff --git a/R/plotD3_halfnormal.R b/R/plotD3_halfnormal.R
@@ -22,12 +22,10 @@
 #' # fit a model
 #' model_lm <- lm(life_length ~ ., data = dragons)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_lm <- DALEX::explain(model_lm, data = dragons, y = dragons$life_length)
+#' lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' hn_lm <- model_halfnormal(exp_lm)
+#' hn_lm <- model_halfnormal(lm_audit)
 #'
 #' # plot results
 #' plotD3_halfnormal(hn_lm)

diff --git a/R/plotD3_lift.R b/R/plotD3_lift.R
@@ -13,31 +13,29 @@
 #' @seealso \code{\link{plot_lift}}
 #'
 #' @examples
-#' library(DALEX)
+#' data(titanic_imputed, package = "DALEX")
 #'
 #' # fit a model
 #' model_glm <- glm(survived ~ ., family = binomial, data = titanic_imputed)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_glm <- explain(model_glm,
+#' glm_audit <- audit(model_glm,
 #'                    data = titanic_imputed,
 #'                    y = titanic_imputed$survived)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' eva_glm <- model_evaluation(exp_glm)
+#' eva_glm <- model_evaluation(glm_audit)
 #'
 #' # plot results
 #' plot_roc(eva_glm)
 #' plot(eva_glm)
 #'
 #' #add second model
 #' model_glm_2 <- glm(survived ~ .-age, family = binomial, data = titanic_imputed)
-#' exp_glm_2 <- explain(model_glm_2,
+#' glm_audit_2 <- audit(model_glm_2,
 #'                      data = titanic_imputed,
 #'                      y = titanic_imputed$survived,
 #'                      label = "glm2")
-#' eva_glm_2 <- model_evaluation(exp_glm_2)
+#' eva_glm_2 <- model_evaluation(glm_audit_2)
 #'
 #' plotD3_lift(eva_glm, eva_glm_2)
 #'

diff --git a/R/plotD3_prediction.R b/R/plotD3_prediction.R
@@ -31,21 +31,19 @@
 #' # fit a model
 #' model_lm <- lm(life_length ~ ., data = dragons)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_lm <- DALEX::explain(model_lm, data = dragons, y = dragons$life_length)
+#' lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' mr_lm <- model_residual(exp_lm)
+#' mr_lm <- model_residual(lm_audit)
 #'
 #' # plot results
 #' plotD3_prediction(mr_lm, abline = TRUE)
 #' plotD3_prediction(mr_lm, variable = "height", smooth = TRUE)
 #'
 #' library(randomForest)
 #' model_rf <- randomForest(life_length~., data = dragons)
-#' exp_rf <- DALEX::explain(model_rf, data = dragons, y = dragons$life_length)
-#' mr_rf <- model_residual(exp_rf)
+#' rf_audit <- audit(model_rf, data = dragons, y = dragons$life_length)
+#' mr_rf <- model_residual(rf_audit)
 #' plotD3_prediction(mr_lm, mr_rf, variable = "weight", smooth = TRUE)
 #'
 #' @export

diff --git a/R/plotD3_rec.R b/R/plotD3_rec.R
@@ -25,18 +25,16 @@
 #' # fit a model
 #' model_lm <- lm(life_length ~ ., data = dragons)
 #'
-#' # use DALEX package to wrap up a model into explainer
-#' exp_lm <- DALEX::explain(model_lm, data = dragons, y = dragons$life_length)
+#' lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)
 #'
 #' # validate a model with auditor
-#' library(auditor)
-#' mr_lm <- model_residual(exp_lm)
+#' mr_lm <- model_residual(lm_audit)
 #' plotD3_rec(mr_lm)
 #'
 #' library(randomForest)
 #' model_rf <- randomForest(life_length~., data = dragons)
-#' exp_rf <- DALEX::explain(model_rf, data = dragons, y = dragons$life_length)
-#' mr_rf <- model_residual(exp_rf)
+#' rf_audit <- audit(model_rf, data = dragons, y = dragons$life_length)
+#' mr_rf <- model_residual(rf_audit)
 #' plotD3_rec(mr_lm, mr_rf)
 #'
 #' @export