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Akashvarma26 · Oct 19, 2024 · c81ec41 · c81ec41
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Showing 10 changed files with 98 additions and 77 deletions.
diff --git a/ann1.h5 b/ann1.h5
diff --git a/app.py b/app.py
@@ -3,10 +3,10 @@
 import pickle
 import tensorflow
 
-model = tensorflow.keras.models.load_model("ann1.h5")
-ohe_geo = pickle.load(open("ohe_geo.pkl", "rb"))
-le_gender = pickle.load(open("le_gender.pkl", "rb"))
-sc = pickle.load(open("sc.pkl", "rb"))
+model = tensorflow.keras.models.load_model("models/ann1.h5")
+ohe_geo = pickle.load(open("preprocessing/ohe_geo.pkl", "rb"))
+le_gender = pickle.load(open("preprocessing/le_gender.pkl", "rb"))
+sc = pickle.load(open("preprocessing/sc.pkl", "rb"))
 
 st.title("Customer Churn Predictor developed by Akashvarma26")
 
@@ -48,9 +48,9 @@
     st.subheader(f"Churn Prediction Result of the customer:")
     st.progress(pred_percent)
     if pred_prob>0.5:
-        st.error(f'⚠️ {name}, the customer is likely to churn with a probability of {pred_prob:.3f}.')
+        st.error(f'⚠️ {name}, the customer is likely to churn. The churn probability is {pred_prob:.3f}.')
     else:
-        st.success(f'✅ {name}, the customer is not likely to churn with a probability of {pred_prob:.3f}.')
+        st.success(f'✅ {name}, the customer is not likely to churn. The churn probability is {pred_prob:.3f}.')
     if credit_score<500:
         st.warning(f"{name}, the credit score is quite low. Customers with low credit scores might have higher churn probabilities.")
     if balance==0:

diff --git a/Churn_Modelling.csv → dataset/Churn_Modelling.csv b/Churn_Modelling.csv → dataset/Churn_Modelling.csv
diff --git a/logs/fit/20241019-115828/train/events.out.tfevents.1729319308.ASUS.7224.0.v2 b/logs/fit/20241019-115828/train/events.out.tfevents.1729319308.ASUS.7224.0.v2
diff --git a/logs/fit/20241019-115828/validation/events.out.tfevents.1729319312.ASUS.7224.1.v2 b/logs/fit/20241019-115828/validation/events.out.tfevents.1729319312.ASUS.7224.1.v2
diff --git a/models/ann1.h5 b/models/ann1.h5
diff --git a/notebook.ipynb b/notebook.ipynb
diff --git a/le_gender.pkl → preprocessing/le_gender.pkl b/le_gender.pkl → preprocessing/le_gender.pkl
diff --git a/ohe_geo.pkl → preprocessing/ohe_geo.pkl b/ohe_geo.pkl → preprocessing/ohe_geo.pkl
diff --git a/sc.pkl → preprocessing/sc.pkl b/sc.pkl → preprocessing/sc.pkl