From ee5a004d4c03ca846d3632b1a6f5e6c5c6ccfeb5 Mon Sep 17 00:00:00 2001
From: Michael Mayer <mayermichael79@gmail.com>
Date: Sat, 20 Sep 2025 15:41:27 +0200
Subject: [PATCH] Random seed should be set before background selection

---
 NEWS.md        | 6 ++++++
 R/kernelshap.R | 9 +++++----
 R/permshap.R   | 8 ++++----
 3 files changed, 15 insertions(+), 8 deletions(-)

diff --git a/NEWS.md b/NEWS.md
index 8209be7..2b5ff4d 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -4,6 +4,12 @@
 
 - More pre-calculations for exact part of the methods ([#175](https://github.com/ModelOriented/kernelshap/pull/175)).
 
+### Bug fixes
+
+- Setting the random seed in `kernelshap()` or `permshap()` would not respect the random selection of the background dataset.
+ ([#177](https://github.com/ModelOriented/kernelshap/pull/177)).
+
+
 # kernelshap 0.9.0
 
 ### Bug fix
diff --git a/R/kernelshap.R b/R/kernelshap.R
index 785ef77..82d6a45 100644
--- a/R/kernelshap.R
+++ b/R/kernelshap.R
@@ -205,16 +205,17 @@ kernelshap.default <- function(
     p == 1L || exact || hybrid_degree %in% 0:(p / 2),
     "m must be even" = trunc(m / 2) == m / 2
   )
+
+  if (!is.null(seed)) {
+    set.seed(seed)
+  }
+
   prep_bg <- prepare_bg(X = X, bg_X = bg_X, bg_n = bg_n, bg_w = bg_w, verbose = verbose)
   bg_X <- prep_bg$bg_X
   bg_w <- prep_bg$bg_w
   bg_n <- nrow(bg_X)
   n <- nrow(X)
 
-  if (!is.null(seed)) {
-    set.seed(seed)
-  }
-
   # Calculate v1 and v0
   bg_preds <- align_pred(pred_fun(object, bg_X, ...))
   v0 <- wcolMeans(bg_preds, bg_w) # Average pred of bg data: 1 x K
diff --git a/R/permshap.R b/R/permshap.R
index d25782f..3e03e1d 100644
--- a/R/permshap.R
+++ b/R/permshap.R
@@ -124,6 +124,10 @@ permshap.default <- function(
     message(txt)
   }
 
+  if (!is.null(seed)) {
+    set.seed(seed)
+  }
+
   basic_checks(X = X, feature_names = feature_names, pred_fun = pred_fun)
   prep_bg <- prepare_bg(X = X, bg_X = bg_X, bg_n = bg_n, bg_w = bg_w, verbose = verbose)
   bg_X <- prep_bg$bg_X
@@ -131,10 +135,6 @@ permshap.default <- function(
   bg_n <- nrow(bg_X)
   n <- nrow(X)
 
-  if (!is.null(seed)) {
-    set.seed(seed)
-  }
-
   # Baseline and predictions on explanation data
   bg_preds <- align_pred(pred_fun(object, bg_X, ...))
   v0 <- wcolMeans(bg_preds, w = bg_w) # Average pred of bg data: 1 x K