Comparative Study On Estimate House Price Using Statistical And Neural Network Model
Azme Bin Khamis, Nur Khalidah Khalilah Binti Kamarudin
Index Terms: multiple linear regression, artificial neural networks, estimate, house price, mean square error, R2, model performance
Abstract: This study was conducted to compare the performance between Multiple Linear Regression (MLR) model and Neural Network model on estimate house prices in New York. A sample of 1047 houses is randomly selected and retrieved from the Math10 website. The factors in prediction house prices including living area, number of bedrooms, number of bathrooms, lot size and age of house. The methods used in this study are MLR and Artificial Neural Network. It was found that, the value of R2 in Neural Network model is higher than MLR model by 26.475%. The value of Mean Squared Error (MSE) in Neural Network model also lower compared to MLR model. Therefore, Neural Network model is prefered to be used as alternative model in estimating house price compared to MLR model.
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