From f6dbd759e6e418b8f0d875b0e92c6c078a111776 Mon Sep 17 00:00:00 2001
From: "Allen Bose(UST" <281879@ust.com>
Date: Mon, 22 Sep 2025 15:48:53 +0530
Subject: [PATCH] week 1 assingment:churned customers trained model

---
 Regression_model.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Regression_model.ipynb b/Regression_model.ipynb
index 71a3782..94fc2d2 100644
--- a/Regression_model.ipynb
+++ b/Regression_model.ipynb
@@ -1938,7 +1938,7 @@
    "cell_type": "markdown",
    "source": [
     "#### Over all performance of the model is 75% ie,our model correctly predicts 75% of all customers.For non churning customers Precision: 92% - When you predict \"won't churn\", we are almost always right.Recall: 72% - You catch 72% of customers who actually stay.Our Model is giving Strong performance for identifying loyal customers.For Churned customers Precision: 51% - Only half your churn predictions are correct Recall: 82% - our  catches 82% of customers who actually churn Good at finding churners, but many false alarms.\n",
-    "#### Strong ares of our mode ls are\n",
+    "#### Strong areas of our model are\n",
     "##### 1).Excellent churn detection (82% recall) - You won't miss many leaving customers\n",
     "##### 2). High confidence in loyal customers (92% precision for non-churn)\n",
     "##### 3).Actionable for retention campaigns\n"
-- 
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