House Rent Prediction Method Based on Decision Tree: Take India as an Example

Authors

  • James Jiayu Guo

DOI:

https://doi.org/10.54097/hbem.v21i.14722

Keywords:

House Rent Prediction, Decision Tree, Time Series Prediction.

Abstract

In this essay, this paper use decision trees to predict house rent and compare it to other linear regressions to find out why decision trees are a good fit for house rent and use house rent data 2023. This paper used the data set from Kaggle which has many factors and is up-to-date for my project, employing some visualization methods on Python to show these factors and their graphs so we can understand some important circumstances about house rent in India. This paper employed three different methods of training models to train them to predict their rent. In the last section, this paper use R2_score, RMSE, MAE and MSE to compare their conclusions. Thus, this paper show why decision trees are the best model for predicting house rent. After all process, this paper proposes that data rent price prediction is very important, because many people don’t have a good obedience on other things like other people’s advice or other black heart house property agents.

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References

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Published

12-12-2023

How to Cite

Guo, J. J. (2023). House Rent Prediction Method Based on Decision Tree: Take India as an Example. Highlights in Business, Economics and Management, 21, 666-671. https://doi.org/10.54097/hbem.v21i.14722