This project focusses mainly on the objective of obtaining house prices by building machine learning models which can help predict for the future assessment of prices based on several factors and to recognize which variables are important for the analysis.
Research Summary
The process of assessing a property's worth for taxation reasons is known as property assessment. The City Assessor's Office in Edmonton is responsible for conducting property assessments. The office employs a number of techniques to establish a property's worth, including examining recent sales of comparable homes, location from a particular place and evaluating the neighborhood real estate market. The property taxes that the owner must pay are determined by the assessed value of the property in Edmonton. The City of Edmonton's Assessment and Tax Tool allows property owners to examine their assessment data online. This research involves using current calendar year's data which helps to build machine learning models for predicting assessed value of the property and selecting the best model for future use. Also, it involves factoring out important variables which are useful for the prediction. Also, some important factors such as Distance from the center, Distance from the green spaces, and distance from the public transport has been utilized to predict the value. After reviewing several models, Neural Network was among the best models which were utilized to predict the property value based on the factors used.
Disclaimer: This website's study design, data analysis, and subsequent results, discussion, and conclusions were created as part of a project for University of Alberta's Ren R 690 course. The assignment's parameters should not be construed outside of them because all data and findings are regarded as preliminary.