Abstract:
House price forecasting is an important topic of real estate. The literature attempts to derive useful knowledge from historical data of property markets. Machine learnin...Show MoreMetadata
Abstract:
House price forecasting is an important topic of real estate. The literature attempts to derive useful knowledge from historical data of property markets. Machine learning techniques are applied to analyze historical property transactions in Australia to discover useful models for house buyers and sellers. Revealed is the high discrepancy between house prices in the most expensive and most affordable suburbs in the city of Melbourne. Moreover, experiments demonstrate that the combination of Stepwise and Support Vector Machine that is based on mean squared error measurement is a competitive approach.
Date of Conference: 03-07 December 2018
Date Added to IEEE Xplore: 17 January 2019
ISBN Information:
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Machine Learning ,
- Learning Algorithms ,
- House Prices ,
- Price Prediction ,
- City Of Melbourne ,
- Housing Price Prediction ,
- Mean Square Error ,
- Support Vector Machine ,
- Machine Learning Techniques ,
- Real Estate ,
- Competitive Approach ,
- City Suburbs ,
- Regression Model ,
- Linear Regression ,
- Neural Network ,
- Housing ,
- Training Data ,
- Decision Tree ,
- Hidden Layer ,
- Data Reduction ,
- Regression Tree ,
- Polynomial Regression ,
- Imputed Values ,
- Land Size ,
- Historical Dataset ,
- Housing Values ,
- Vector Autoregressive Model ,
- Real Estate Agents ,
- Real Estate Market ,
- Radial Basis Function
- Author Keywords
Contents Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Machine Learning ,
- Learning Algorithms ,
- House Prices ,
- Price Prediction ,
- City Of Melbourne ,
- Housing Price Prediction ,
- Mean Square Error ,
- Support Vector Machine ,
- Machine Learning Techniques ,
- Real Estate ,
- Competitive Approach ,
- City Suburbs ,
- Regression Model ,
- Linear Regression ,
- Neural Network ,
- Housing ,
- Training Data ,
- Decision Tree ,
- Hidden Layer ,
- Data Reduction ,
- Regression Tree ,
- Polynomial Regression ,
- Imputed Values ,
- Land Size ,
- Historical Dataset ,
- Housing Values ,
- Vector Autoregressive Model ,
- Real Estate Agents ,
- Real Estate Market ,
- Radial Basis Function
- Author Keywords
