Update app.py

app.py

@@ -371,26 +371,5 @@ logging.info(f"Prophet Model - MAE: {mae:.4f}")
 
 
 
-# Features for promotion prediction
-features = ['caption_length', 'hashtag_count', 'sentiment', 'content_type_encoded', 'media_type_encoded']
-X = solved_df[features]
-y = solved_df['promote']
-
-# Split data into training and testing sets
-X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
-
-# Train a Logistic Regression Model
-promotion_model = LogisticRegression(random_state=42)
-promotion_model.fit(X_train, y_train)
-
-# Evaluate the model
-y_pred = promotion_model.predict(X_test)
-accuracy = accuracy_score(y_test, y_pred)
-logging.info(f"Promotion Prediction Model Accuracy: {accuracy:.4f}")
-
-# Analyze content type impact
-content_type_impact = solved_df.groupby('content_type')['promote'].mean().sort_values(ascending=False)
-logging.info("Content Type Impact on Promotion:")
-print(content_type_impact)
 
 logging.info("Analysis complete!")