Machine learning housing price prediction in petaling jaya, Selangor, Malaysia

Abstract

This paper demonstrates the utilization of machine learning algorithms in the prediction of housing selling prices on real dataset collected from the Petaling Jaya area, Selangor, Malaysia. To date, literature about research on machine learning prediction of housing selling price in Malaysia is scarce. This paper provides a brief review of the existing machine learning algorithms for the prediction problem and presents the characteristics of the collected datasets with different groups of feature selection. The findings indicate that using irrelevant features from the dataset can decrease the accuracy of the prediction models.