Data-Driven House Price Prediction Models

Abstract

The real estate market is outstanding the most important thing is the price, which is always changing. that one of the main areas of application of mechanical ideas learn how to increase and predict high costs accuracy. The purpose of this work is market value of real estate. This system will help you find the property's starting price based on geographic variables. By breaking past markets patterns and value ranges and future advances expected future costs. The meaning of this test is predicting real estate prices using decision trees regressor. Helps customers invest resources in legacy without contacting a broker. The result research has shown that decision tree regressors give the following results: Accuracy 89%.