From 6761957908e0c80679fec3281b7a13e8f64112ce Mon Sep 17 00:00:00 2001 From: user_client2024 Date: Mon, 22 Sep 2025 12:03:17 +0000 Subject: [PATCH] System save at 22/09/2025 17:33 by user_client2024 --- .ipynb_checkpoints/main-checkpoint.ipynb | 4 ++-- main.ipynb | 4 ++-- main.py | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/.ipynb_checkpoints/main-checkpoint.ipynb b/.ipynb_checkpoints/main-checkpoint.ipynb index f8bb87d..6cf5f8b 100644 --- a/.ipynb_checkpoints/main-checkpoint.ipynb +++ b/.ipynb_checkpoints/main-checkpoint.ipynb @@ -29,8 +29,8 @@ " \"\"\"\n", "\n", " # Calculate thresholds\n", - " th1 = np.percentile(df[var1].dropna(), 80)\n", - " th2 = np.percentile(df[var2].dropna(), 80)\n", + " th1 = np.percentile(df[var1].dropna(), 90)\n", + " th2 = np.percentile(df[var2].dropna(), 90)\n", " th3 = np.percentile(df[var3].dropna(), 90)\n", "\n", " # Split into alerting and non-alerting\n", diff --git a/main.ipynb b/main.ipynb index f8bb87d..6cf5f8b 100644 --- a/main.ipynb +++ b/main.ipynb @@ -29,8 +29,8 @@ " \"\"\"\n", "\n", " # Calculate thresholds\n", - " th1 = np.percentile(df[var1].dropna(), 80)\n", - " th2 = np.percentile(df[var2].dropna(), 80)\n", + " th1 = np.percentile(df[var1].dropna(), 90)\n", + " th2 = np.percentile(df[var2].dropna(), 90)\n", " th3 = np.percentile(df[var3].dropna(), 90)\n", "\n", " # Split into alerting and non-alerting\n", diff --git a/main.py b/main.py index 7100d06..7d38ee2 100644 --- a/main.py +++ b/main.py @@ -26,8 +26,8 @@ def apply_sar_flag(df, var1, var2, var3, random_state=42): """ # Calculate thresholds - th1 = np.percentile(df[var1].dropna(), 80) - th2 = np.percentile(df[var2].dropna(), 80) + th1 = np.percentile(df[var1].dropna(), 90) + th2 = np.percentile(df[var2].dropna(), 90) th3 = np.percentile(df[var3].dropna(), 90) # Split into alerting and non-alerting