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首页多元线性回归驱动的房价预测:买卖双赢策略
多元线性回归驱动的房价预测:买卖双赢策略
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更新于2023-05-02
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本篇研究论文《使用多元线性回归的房价预测》由Anirudh Kaushal和Achyut Shankar撰写,发表于印度阿米提大学工程与技术学院计算机科学与工程系。两位作者探讨了在房地产市场中,房价预测对于买家和卖家都具有实际价值的重要性。 论文的核心主题是通过多元线性回归模型来精确估算房屋价格。在日常生活中,无论是购房者寻找心仪的房子还是卖家想提升房屋的销售价格,准确的价格预测都是关键。购房者可以根据自己的需求,如房屋面积、卧室数量、地理位置、设施等特征,利用机器学习技术,通过多元线性回归算法来获取房屋的预期价格。这不仅可以帮助消费者做出更明智的购买决策,还能减少市场信息不对称带来的困扰。 论文详细介绍了如何收集和处理相关的经济、地理和社会因素数据,这些因素可能影响房价,如经济发展水平、就业率、学区质量等。通过构建数学模型,论文展示了如何将这些变量转化为预测模型中的权重,以预测特定房屋的市场价值。同时,也讨论了模型的建立、训练过程以及如何评估其预测精度,包括可能的误差分析和模型优化策略。 在实际应用层面,论文提出了一种用户友好的界面,使得用户能够方便地输入他们想要购买的房屋属性,系统会实时返回一个基于多元线性回归预测的房价估计。这种工具不仅简化了购房过程,也为房地产市场的参与者提供了有力的定价依据。 《使用多元线性回归的房价预测》这篇论文不仅深入探讨了房价预测在房地产交易中的作用,还提供了一种实用的方法论,展示了如何通过统计学和机器学习技术来解决实际生活中的房屋价值评估问题。对于研究人员、房地产从业者以及潜在的购房者和卖家来说,这篇论文都具有很高的参考价值。
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House Price Prediction Using Multiple Linear
Regression
Anirudh Kaushal, Achyut Shankar
Department of Computer Science and Engineering, Amity School of Engineering and
Technology, Amity University, Noida, Uttar Pradesh, India
anirudhkushal30@gmail.com, ashankar2711@gmail.com
Abstract. There comes a point in everyone’s life when the person wishes to buy
or sell a house. First consider a scenario where a person needs to buy a house. The
person will look for his/her desired house for a sensible price tag. The person will
have some features decided what he/she wants to have in the house. The person
will be able to decide whether the type of house he/she is looking for is worth of
the price or not.
Similarly, consider a scenario where a person needs to sell a house. By making
use of the house price prediction system, the seller would be able to decide what
all features he/she could add in the house so that the house can be sold for a higher
price. Hence, from both the above scenarios we can confirm that house price
prediction is useful both for the buyer and seller.
This paper will help to predict the house prices based on various parameters. The
users will be able to input the type of house they desire to buy and with the help
of machine learning the house price predictor will display the estimated price of
the desired house.
Keywords: House Price Prediction, Machine Learning, Multiple Linear Regression
1
INTRODUCTION
Usually when people want to buy a house, they look for a house which has a reasonable
cost, and which has all the desired features they want in the house. The house price
prediction will help them to decide whether the house they desire to buy is worth of the
price or not. Similar is the case with people who want to sell the house. By making use
of the house price prediction system, the seller would be able to decide what all features
he/she could add in the house so that the house can be sold for a higher price.
This paper’s objective is predicting house prices on the basis of various parameters.
This will allow the buyer to get an idea of what amount of money he/she has to spend in
order to buy the desired house. It will also allow the seller to get information regarding
what is the house’s real worth and how he/she can maximize the profit gained by selling
the house.
There are many platforms which help the buyers and sellers to predict the price of
the property they are desire and the property they are looking for. Some of them are
MagicBricks and 99acres. They allow the user to enter the locality of the house any-
where in India along with all the other features thus making the house price prediction
system more effective.
Electronic copy available at: https://ssrn.com/abstract=3833734
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