# Importing Streamlit for building the web-based interactive application framework import streamlit as st # Function to Display Model Performance def display_hybrid_model_performance(): # Basic HTML table without additional styling html_content = """
Regression Model Performance Overview

This table presents the performance of various regression models for different companies.

Model MAE MSE RMSE R² Score Accuracy (%)
MLP 4.631412 30.276025 5.502365 0.583915 99.863574
Linear Regression 5.725293 39.196283 6.260694 0.461323 100.000000
K-Nearest Neighbors (KNN) 5.575181 41.867105 6.470479 0.424618 100.000000
SVM 5.771079 47.432490 6.887125 0.348132 99.454297
Gradient Boosting 6.189361 52.197185 7.224762 0.282651 100.000000
Random Forest 6.378920 60.091005 7.751839 0.174165 100.000000
Decision Tree 6.405307 61.140660 7.819249 0.159740 100.000000
AdaBoost 7.360769 77.328544 8.793665 -0.062731 100.000000
""" # Display the HTML content st.markdown(html_content, unsafe_allow_html=True)