House Price Prediction using Machine Learning

Authors

Presenter(s)

Sai Surya Vaddi, Amira A. Yousif

Comments

Presentation: 11:00 a.m.-11:20 a.m., Kennedy Union 211

This project reflects research conducted as part of a course project designed to give students experience in the research process.

Course: CPS 595

Files

Description

In this research, we investigate the usage of machine learning in predicting the house price based on related tabular data and images.To this end, we collect 2000 sample points from across different cites in the United States. For each house, we label 14 tabular attributes and 5 images (exterior, interior-living room, kitchen, bedroom, bathroom). Following the feature extraction, we evaluate different machine learning methods on the newly collected data.

Publication Date

4-20-2022

Project Designation

Course Project

Primary Advisor

Van Tam Nguyen

Primary Advisor's Department

Computer Science

Keywords

Stander Symposium project, College of Arts and Sciences

United Nations Sustainable Development Goals

Decent Work and Economic Growth

Recommended Citation

"House Price Prediction using Machine Learning" (2022). Stander Symposium Projects. 2462.
https://ecommons.udayton.edu/stander_posters/2462