Machine Learning for Improved Automated Valuation Model

According to “Standard on Automated Valuation Models (AVMs)”, an automated valuation model (AVM) is a mathematically based computer software program that produces an estimate of market value based on market analysis of location, market conditions, and real estate characteristics from information that was previously and separately collected. The purpose of an AVM is to provide a credible, reliable, and cost-effective estimate of market value as of a given point in time. Residential real estate market is geographically diverse and constantly changing. Traditional regression models require a long time to build and are rarely updated to reflect changes in the dynamic environment. Data Nerds at Kelowna initiated an internship project with UBCO to apply machine learning techniques for a more accurate and reliable valuation model. The outcome of the project will be integrated into Data Nerds’ AVM application platform.

Faculty Supervisor:

Zheng Liu;Eric Li

Student:

Partner:

Data Nerds

Discipline:

Engineering

Sector:

Information and cultural industries

University:

University of British Columbia - Okanagan

Program: