🔍 Problem Description:
I want to predict heat and cool load of a building which is really necessary while planning design of a building . It depends on several factors such as relative compactness area and some more

🧠 Model Description:
Our model will be based on randomforestclassifier and also will be enhanced by XGBoost
⏲️ Estimated Time for Completion:
It will take approximately a week for me to completely implement this
🎯 Expected Outcome:
After implementation we will be able to predict head and cooling load of a building
📄 Additional Context:
I will also implement ensemble learning

To be Mentioned while taking the issue:

• What is your participant role? <!-- GSSoC 2024 extended contributor

Note:

• Please review the project documentation and ensure your code aligns with the project structure.
• Please ensure that either the predict.py file includes a properly implemented model_details() function or the notebook contains this function to print a detailed model report. The model will not be accepted without this function in place, as it is essential for generating the necessary model details.
• Prefer using a new branch to resolve the issue, as it helps keep the main branch stable and makes it easier to manage and review your changes.
• Strictly use the pull request template provided in the repository to create a pull request.