Automation of Real estate Market Pridiction

Rohit Singh

Abstract


The real estate market is a standout amongst the most focused regarding pricing and keeps fluctuating. It is one of the prime fields to apply the ideas of machine learning on how to enhance and foresee the costs with high accuracy. The objective of the paper is the prediction of the market value of a real estate property. This system helps find a starting price for a property based on geographical variables. By breaking down past market patterns and value ranges, and coming advancements future costs will be anticipated. It will help clients to put resources into a bequest without moving toward a broker. The result of this research proved that the Decision tree regressor gives an accuracy of 89%.

Keywords


Decision tree regressor, machine learning

References


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