多元线性回归和随机森林对房价估计的性能分析

2022 International Seminar on Application for Technology of Information and Communication (iSemantic) Pub Date : 2022-09-17 DOI:10.1109/iSemantic55962.2022.9920454

Sukma Ayu Septianingrum, M. Alfian Dzikri, M. Soeleman, Pujiono Pujiono, M. Muslih

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引用次数: 1

摘要

房子是人类需要的木板。房价每年都在持续上涨，这使得一些人很难根据自己的经济能力买房。大城市的许多房地产开发商继续建造住房，包括南雅加达地区，那里有许多新移民。在本研究中，我们将使用多元线性回归和随机森林两种方法的比较来预测房价，训练数据和测试数据的RMSE值为8:2，并且多元线性回归方法产生的误差更小。8:2实验得到线性回归的RMSE为3673441811.575，随机森林的RMSE为3693111743.726。

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Performance Analysis of Multiple Linear Regression and Random Forest for an Estimate of the Price of a House

The house is a human need for boards. House prices that continue to rise every year make it difficult for some people to buy a house according to their respective financial capabilities. Many property developers in big cities continue to build housing, including the South Jakarta area with many new arrivals. In this study, we will predict house prices using a comparison of 2 methods, multiple linear regression and random forest which produces a better RMSE value at an 8:2 comparison between training data and testing data, and the multiple linear regression method produces fewer errors. The 8:2 experiment produces an RMSE 3673441811.575 of Linear Regression and 3693111743.726 of Random Forest.

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2022 International Seminar on Application for Technology of Information and Communication (iSemantic)

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