Abstract House Price Index (HPI) is commonly used to estimate the changes in housing
price. Since housing price is strongly correlated to other factors such as location, area …

Housing price prediction in real estate industry is a very difficult task, and it has piqued the
interest of many researchers over the past years in the quest to look for a suitable model to …

Data mining is now commonly applied in the real estate market. Data mining's ability to
extract relevant knowledge from raw data makes it very useful to predict house prices, key …

Profound insights have been gained into which characteristics determine housing prices.
These characteristics reflect two different aspects: those which are correlated with the …

Predictive models for determining the sale price of houses in cities like Bengaluru is still
remaining as more challenging and tricky task. The sale price of properties in cities like …

Property valuation plays a significant role in urban economics and is of great importance to
various stakeholders who interact and shape the city, including property owners, buyers …

Purpose The purpose of this study to apply stacking ensemble machine learning algorithm
for predicting the cost of highway construction projects. Design/methodology/approach The …

Purpose The purpose of this paper is to investigate the accuracy and volatility of different
methods for estimating and updating hedonic valuation models. Design/methodology …

Accurate price evaluation of real estate is beneficial for many parties involved in real estate
business such as real estate companies, property owners, investors, banks, and financial …

Now a days house resale is majorly seen in metro cities. The market demand for housing is
always increasing every year due to increase in population and migrating to other cities for …