restore \donttest

ModelOriented · Sep 29, 2023 · 2b8b65c · 2b8b65c
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diff --git a/R/plot_contribution.R b/R/plot_contribution.R
@@ -26,6 +26,7 @@
 #'
 #'
 #' @examples
+#' \donttest{
 #' library(xgboost)
 #' data <- fifa20$data[colnames(fifa20$data) != 'work_rate']
 #' target <- fifa20$target
@@ -36,6 +37,7 @@
 #' x <- head(data, 1)
 #' shap <- treeshap(unified_model, x)
 #' plot_contribution(shap, 1,  min_max = c(0, 120000000))
+#' }
 plot_contribution <- function(treeshap,
                               obs = 1,
                               max_vars = 5,

diff --git a/R/plot_feature_dependence.R b/R/plot_feature_dependence.R
@@ -20,6 +20,7 @@
 #'
 #'
 #' @examples
+#' \donttest{
 #' library(xgboost)
 #' data <- fifa20$data[colnames(fifa20$data) != 'work_rate']
 #' target <- fifa20$target
@@ -30,6 +31,7 @@
 #' x <- head(data, 100)
 #' shaps <- treeshap(unified_model, x)
 #' plot_feature_dependence(shaps, variable = "overall")
+#' }
 plot_feature_dependence <- function(treeshap, variable,
                                     title = "Feature Dependence", subtitle = NULL) {
 

diff --git a/R/plot_interaction.R b/R/plot_interaction.R
@@ -22,13 +22,15 @@
 #'
 #'
 #' @examples
+#' \donttest{
 #' data <- fifa20$data[colnames(fifa20$data) != 'work_rate']
 #' target <- fifa20$target
 #' param2 <- list(objective = "reg:squarederror", max_depth = 5)
 #' xgb_model2 <- xgboost::xgboost(as.matrix(data), params = param2, label = target, nrounds = 10)
 #' unified_model2 <- xgboost.unify(xgb_model2, data)
 #' inters <- treeshap(unified_model2, as.matrix(data[1:50, ]), interactions = TRUE)
 #' plot_interaction(inters, "dribbling", "defending")
+#' }
 plot_interaction <- function(treeshap, var1, var2,
                              title = "SHAP Interaction Value Plot",
                              subtitle = "") {

diff --git a/R/predict.R b/R/predict.R
@@ -11,6 +11,7 @@
 #' @export
 #'
 #' @examples
+#' \donttest{
 #' library(gbm)
 #' data <- fifa20$data[colnames(fifa20$data) != 'work_rate']
 #' data['value_eur'] <- fifa20$target
@@ -23,6 +24,7 @@
 #'   n.cores = 1)
 #'   unified <- gbm.unify(gbm_model, data)
 #'   predict(unified, data[2001:2005, ])
+#'   }
 predict.model_unified <- function(object, x, ...) {
   unified_model <- object
   model <- unified_model$model

diff --git a/R/set_reference_dataset.R b/R/set_reference_dataset.R
@@ -26,6 +26,7 @@
 #' \code{\link{randomForest.unify}} for \code{\link[randomForest:randomForest]{randomForest models}}
 #'
 #' @examples
+#' \donttest{
 #' library(gbm)
 #' data <- fifa20$data[colnames(fifa20$data) != 'work_rate']
 #' data['value_eur'] <- fifa20$target
@@ -38,6 +39,7 @@
 #'   n.cores = 1)
 #' unified <- gbm.unify(gbm_model, data)
 #' set_reference_dataset(unified, data[200:700, ])
+#' }
 set_reference_dataset <- function(unified_model, x) {
   model <- unified_model$model
   data <- x

diff --git a/R/unify_gbm.R b/R/unify_gbm.R
@@ -21,6 +21,7 @@
 #' \code{\link{randomForest.unify}} for \code{\link[randomForest:randomForest]{randomForest models}}
 #'
 #' @examples
+#' \donttest{
 #' library(gbm)
 #' data <- fifa20$data[colnames(fifa20$data) != 'work_rate']
 #' data['value_eur'] <- fifa20$target
@@ -34,6 +35,7 @@
 #' unified_model <- gbm.unify(gbm_model, data)
 #' shaps <- treeshap(unified_model, data[1:2,])
 #' plot_contribution(shaps, obs = 1)
+#' }
 gbm.unify <- function(gbm_model, data) {
   if(!inherits(gbm_model,'gbm')) {
     stop('Object gbm_model was not of class "gbm"')

diff --git a/R/unify_lightgbm.R b/R/unify_lightgbm.R
@@ -25,6 +25,7 @@
 #' \code{\link{randomForest.unify}} for \code{\link[randomForest:randomForest]{randomForest models}}
 #'
 #' @examples
+#' \donttest{
 #' library(lightgbm)
 #' param_lgbm <- list(objective = "regression", max_depth = 2,
 #'                    force_row_wise = TRUE, num_iterations = 20)
@@ -40,6 +41,7 @@
 #' unified_model <- lightgbm.unify(lgb_model, sparse_data)
 #' shaps <- treeshap(unified_model, data[1:2, ])
 #' plot_contribution(shaps, obs = 1)
+#' }
 lightgbm.unify <- function(lgb_model, data, recalculate = FALSE) {
   if (!requireNamespace("lightgbm", quietly = TRUE)) {
     stop("Package \"lightgbm\" needed for this function to work. Please install it.",

diff --git a/R/unify_xgboost.R b/R/unify_xgboost.R
@@ -21,6 +21,7 @@
 #' \code{\link{randomForest.unify}} for \code{\link[randomForest:randomForest]{randomForest models}}
 #'
 #' @examples
+#' \donttest{
 #' library(xgboost)
 #' data <- fifa20$data[colnames(fifa20$data) != 'work_rate']
 #' target <- fifa20$target
@@ -30,6 +31,7 @@
 #' unified_model <- xgboost.unify(xgb_model, as.matrix(data))
 #' shaps <- treeshap(unified_model, data[1:2,])
 #' plot_contribution(shaps, obs = 1)
+#' }
 #'
 xgboost.unify <- function(xgb_model, data, recalculate = FALSE) {
   if (!requireNamespace("xgboost", quietly = TRUE)) {

diff --git a/man/gbm.unify.Rd b/man/gbm.unify.Rd
diff --git a/man/lightgbm.unify.Rd b/man/lightgbm.unify.Rd
diff --git a/man/plot_contribution.Rd b/man/plot_contribution.Rd
diff --git a/man/plot_feature_dependence.Rd b/man/plot_feature_dependence.Rd
diff --git a/man/plot_interaction.Rd b/man/plot_interaction.Rd
diff --git a/man/predict.model_unified.Rd b/man/predict.model_unified.Rd
diff --git a/man/set_reference_dataset.Rd b/man/set_reference_dataset.Rd
diff --git a/man/xgboost.unify.Rd b/man/xgboost.unify.Rd