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app.py

@@ -12,7 +12,7 @@ model = joblib.load(model_path)
 # Streamlit UI for Customer Churn Prediction
 st.title("Engine Predictive Maintenance App")
 st.write("Engine Predictive Maintenance App is a tool to predicts whether an engine will fail or not based on the engine health parameters.")
-st.write("Kindly enter the enging parameters.")
+st.write("Please enter the Enging parameters.")
 
 # Get the inputs and save them into a dataframe
 Engine_rpm = st.number_input("Engine rpms", min_value=0, max_value=5000, value=500)
@@ -33,7 +33,7 @@ input_data = pd.DataFrame([{
 }])
 
 # Set the classification threshold
-classification_threshold = 0.45
+classification_threshold = 0.425
 
 # Predict button
 if st.button("Predict"):