基于机器学习模型的商业地产估值

I. Astrakhantseva, N. V. Smirnova
{"title":"基于机器学习模型的商业地产估值","authors":"I. Astrakhantseva, N. V. Smirnova","doi":"10.38197/2072-2060-2022-237-5-34-57","DOIUrl":null,"url":null,"abstract":"Based on the interests of users and compliance with the legislation in the field of valuation, the authors propose the use of machine learning methods in valuation practice for the valuation of commercial real estate. Five regression methods were chosen as the algorithms on which the model works. The proposed machine learning model can be trained and improved based on its own experience in an automatic mode without explicit human participation. The target indicator of the model is the “price per sq. m” and “rental rate” of commercial real estate.","PeriodicalId":395765,"journal":{"name":"Scientific Works of the Free Economic Society of Russia","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"COMMERCIAL REAL ESTATE VALUATION BASED ON MACHINE LEARNING MODELS\",\"authors\":\"I. Astrakhantseva, N. V. Smirnova\",\"doi\":\"10.38197/2072-2060-2022-237-5-34-57\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the interests of users and compliance with the legislation in the field of valuation, the authors propose the use of machine learning methods in valuation practice for the valuation of commercial real estate. Five regression methods were chosen as the algorithms on which the model works. The proposed machine learning model can be trained and improved based on its own experience in an automatic mode without explicit human participation. The target indicator of the model is the “price per sq. m” and “rental rate” of commercial real estate.\",\"PeriodicalId\":395765,\"journal\":{\"name\":\"Scientific Works of the Free Economic Society of Russia\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Works of the Free Economic Society of Russia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.38197/2072-2060-2022-237-5-34-57\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Works of the Free Economic Society of Russia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.38197/2072-2060-2022-237-5-34-57","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

基于用户的利益和符合估值领域的立法,作者提出在估值实践中使用机器学习方法对商业地产进行估值。选择了五种回归方法作为模型工作的算法。提出的机器学习模型可以在没有人类明确参与的情况下,根据自己的经验在自动模式下进行训练和改进。该模型的目标指标是“每平方价格”。M”和商业地产的“租金率”。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
COMMERCIAL REAL ESTATE VALUATION BASED ON MACHINE LEARNING MODELS
Based on the interests of users and compliance with the legislation in the field of valuation, the authors propose the use of machine learning methods in valuation practice for the valuation of commercial real estate. Five regression methods were chosen as the algorithms on which the model works. The proposed machine learning model can be trained and improved based on its own experience in an automatic mode without explicit human participation. The target indicator of the model is the “price per sq. m” and “rental rate” of commercial real estate.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信