From 100795c576487d191004d44d3469eb53bbf7a048 Mon Sep 17 00:00:00 2001
From: "sonarqube-agent[bot]"
 <210722872+sonarqube-agent[bot]@users.noreply.github.com>
Date: Wed, 20 May 2026 10:13:49 +0000
Subject: [PATCH] fix: Address SonarQube issue

Fixed issues:
- AZ45C1YORXnEWm2Rf6TT for python:S5797 rule

Generated by SonarQube Agent (task: 6697a24c-a9d0-46ec-bf23-33f308392970)
---
 benchmarks/bench_isolation_forest.py | 12 ------------
 1 file changed, 12 deletions(-)

diff --git a/benchmarks/bench_isolation_forest.py b/benchmarks/bench_isolation_forest.py
index 99a89989cc1bb..2d4879eaa8d92 100644
--- a/benchmarks/bench_isolation_forest.py
+++ b/benchmarks/bench_isolation_forest.py
@@ -48,9 +48,6 @@ def print_outlier_ratio(y):
 random_state = 1
 fig_roc, ax_roc = plt.subplots(1, 1, figsize=(8, 5))
 
-# Set this to true for plotting score histograms for each dataset:
-with_decision_function_histograms = False
-
 # datasets available = ['http', 'smtp', 'SA', 'SF', 'shuttle', 'forestcover']
 datasets = ["http", "smtp", "SA", "SF", "shuttle", "forestcover"]
 
@@ -132,15 +129,6 @@ def print_outlier_ratio(y):
     scoring = -model.decision_function(X_test)  # the lower, the more abnormal
 
     print("--- Preparing the plot elements...")
-    if with_decision_function_histograms:
-        fig, ax = plt.subplots(3, sharex=True, sharey=True)
-        bins = np.linspace(-0.5, 0.5, 200)
-        ax[0].hist(scoring, bins, color="black")
-        ax[0].set_title("Decision function for %s dataset" % dat)
-        ax[1].hist(scoring[y_test == 0], bins, color="b", label="normal data")
-        ax[1].legend(loc=LEGEND_LOC)
-        ax[2].hist(scoring[y_test == 1], bins, color="r", label="outliers")
-        ax[2].legend(loc=LEGEND_LOC)
 
     # Show ROC Curves
     predict_time = time() - tstart