nawarturk/wait_time_estimator

Game Lobby Wait Time Estimator

Welcome to the Wait Time Estimator project, developed as part of the ConUHacks VIII hackathon challenge hosted by Behaviour Interactive.

Project Overview

This web application is designed to estimate wait times for a game lobby. It leverages a supervised regression model created using Flask and Python for the backend, and JavaScript, HTML, and CSS for the frontend.

For more information about ConUHacks VIII, visit ConUHacks.

Getting Started

To get started with the Game Lobby Wait Time Estimator, follow these steps:

1. Clone the Repository: Clone this repository to your local machine using the following command:

   git clone https://github.com/NawarTurk/Wait_Time_Estimator.git
   

2. Navigate to the Project Directory: Change your current directory to the root of the project.

3. Run the Flask Application: You'll need to run the Flask application at the root of the project directory. Use the following command ( This will start the web application locally. ):

   flask run
   

4. Upload and Train Historical Data To use the wait time estimation model, you should upload and train it using historical data. A mock historical data file, 'Mock Historical Data.csv,' is provided in the repository. Ensure that your data file follows the same format as the mock file.

5. Add Additional Feature Values
   If you have additional possible values for different features, you can incorporate them by extending the encode_dataframe(df) function in the train_model.py file.

Key Insights and Areas for Enhancement

Experiment with different algorithms (Decision Trees, Random Forests, Neural Networks) to improve prediction accuracy. Consider enhancing the frontend and visualization for a better user experience. Thank you for exploring our project, and we hope it proves valuable in estimating game lobby wait times. Feel free to contribute and enhance this project further!