{"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}
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.