Abstract
The study examines the use of multi layer perception network (MLP) in predicting the price of terrace houses in Kuala Lumpur (KL). Nine factors that significantly influence the price were used in this attempt. Housing data from 1994 to 1996 were presented to the network for training. Tested results from the model obtained for various years were compared using regression analysis. The study provides the predictive ability of the trained MLP model that can be used as an alternative predictor in real estate analysis.
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