Model agnostic interpretable machine learning for residential property valuation

IF 1.2 4区地球科学 Q3 ENGINEERING, CIVIL

Survey Review Pub Date : 2023-12-18 DOI:10.1080/00396265.2023.2293366

Tugba Gunes

引用次数: 0

Abstract

Machine learning algorithms commonly outperform the traditional hedonic models in property valuation; however, it is hard to capture the inner workings of these complex models due to their black-bo...

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用于住宅物业估价的与模型无关的可解释机器学习

机器学习算法在房地产估价方面通常优于传统的享乐主义模型；然而，由于这些复杂模型的黑箱操作，很难捕捉其内部运作。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Survey Review 地学-地球科学综合

CiteScore

3.50

自引率

6.20%

发文量

审稿时长

6 months

期刊介绍： Survey Review is an international journal that has been published since 1931, until recently under the auspices of the Commonwealth Association of Surveying and Land Economy (CASLE). The journal is now published for Survey Review Ltd and brings together research, theory and practice of positioning and measurement, engineering surveying, cadastre and land management, and spatial information management. All papers are peer reviewed and are drawn from an international community, including government, private industry and academia. Survey Review is invaluable to practitioners, academics, researchers and students who are anxious to maintain their currency of knowledge in a rapidly developing field.