House Price Prediction Using Machine Learning Algorithms

被引：4

作者：

Vineeth, Naalla ^{[1
]}

Ayyappa, Maturi ^{[1
]}

Bharathi, B. ^{[1
]}

机构：

[1] Sathyabama Inst Sci & Technol, Comp Sci & Engn, Chennai, Tamil Nadu, India

来源：

SOFT COMPUTING SYSTEMS, ICSCS 2018 | 2018年 / 837卷

关键词：

House price index; Simple linear regression (SLR); Multiple linear regression (MLR); Neural networks (NN); Mean square error (MSE);

D O I：

10.1007/978-981-13-1936-5_45

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Due to increase in urbanization, there is an increase in demand for renting houses and purchasing houses. Therefore, to determine a more effective way to calculate house price that accurately reflects the market price becomes a hot topic. The paper focuses on finding the house price accurately by using machine learning algorithms like simple linear regression (SLR), Multiple linear regression (MLR), Neural Networks (NN). The algorithm which has the lower Mean Square Error (MSE) is chosen as the best algorithm for predicting the house price. This will be helpful for both the sellers and buyers for finding the best price for the house.

引用

页码：425 / 433

页数：9

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