Update app.py

app.py

@@ -1,8 +1,7 @@
 from flask import Flask, render_template, request
 import pandas as pd
 from sklearn.linear_model import LogisticRegression
-from sklearn.pipeline import make_pipeline
-from sklearn.preprocessing import StandardScaler
+
 
 app = Flask(__name__)
 
@@ -15,8 +14,8 @@ X = iris[['sepal_length', 'sepal_width', 'petal_length', 'petal_width']]
 y = iris['species']
 
 
-# Create pipeline: Scaling + Logistic Regression
-model = make_pipeline(StandardScaler(), LogisticRegression())
+# Logistic Regression
+model = LogisticRegression()
 model.fit(X, y)  # Train once
 
 @app.route('/')