Comparison of Ensemble Learning Models with Expert Algorithms Designed for a Property Valuation System

被引：4
|
作者：
Trawinski, Bogdan [1 ]
Lasota, Tadeusz [2 ]
Kempa, Olgierd [2 ]
Telec, Zbigniew [1 ]
Kutrzynski, Marcin [1 ]
机构：
[1] Wroclaw Univ Sci & Technol, Fac Comp Sci & Management, Wroclaw, Poland
[2] Wroclaw Univ Environm & Life Sci, Dept Spatial Management, Wroclaw, Poland
来源：
COMPUTATIONAL COLLECTIVE INTELLIGENCE, ICCCI 2017, PT I | 2017年 / 10448卷
关键词：
Machine learning; Ensemble models; Sales comparison approach; Expert algorithms; Property valuation; Mass appraisal; MASS APPRAISAL; BAGGING ENSEMBLES; FUZZY MODELS;
D O I：
10.1007/978-3-319-67074-4_31
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Three expert algorithms based on the sales comparison approach worked out for an automated system to aid in real estate appraisal are presented in the paper. Ensemble machine learning models and expert algorithms for real estate appraisal were compared empirically in terms of their accuracy. The evaluation experiments were conducted using real-world data acquired from a cadastral system maintained in a big city in Poland. The characteristics of applied techniques for real estate appraisal are discussed.
引用
收藏
页码：317 / 327
页数：11
相关论文
共 50 条
  • [1] Comparison of Expert Algorithms with Machine Learning Models for Real Estate Appraisal
    Trawinski, Bogdan
    Telec, Zbigniew
    Krasnoborski, Jacek
    Piwowarczyk, Mateusz
    Talaga, Michal
    Lasota, Tedeusz
    Sawilow, Edward
    2017 IEEE INTERNATIONAL CONFERENCE ON INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS (INISTA), 2017, : 51 - 54
  • [2] Property valuation using machine learning algorithms on statistical areas in Greater Sydney, Australia
    Gao, Qishuo
    Shi, Vivien
    Pettit, Christopher
    Han, Hoon
    LAND USE POLICY, 2022, 123
  • [3] Spatial Performance Approach to Machine Learning Algorithms: A GIS-Based Comparison Analysis for Real Estate Valuation
    Genc, Nihal
    Colak, H. Ebru
    Ozbilgin, Ferdi
    TRANSACTIONS IN GIS, 2025, 29 (01)
  • [4] Developing automated valuation models for estimating property values: a comparison of global and locally weighted approaches
    Doumpos, Michalis
    Papastamos, Dimitrios
    Andritsos, Dimitrios
    Zopounidis, Constantin
    ANNALS OF OPERATIONS RESEARCH, 2021, 306 (1-2) : 415 - 433
  • [5] Automated real estate valuation with machine learning models using property descriptions
    Baur, Katharina
    Rosenfelder, Markus
    Lutz, Bernhard
    EXPERT SYSTEMS WITH APPLICATIONS, 2023, 213
  • [6] An Ensemble Approach for Intrusion Detection System Using Machine Learning Algorithms
    Gautam, Rohit Kumar Singh
    Doegar, Er Amit
    PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE CONFLUENCE 2018 ON CLOUD COMPUTING, DATA SCIENCE AND ENGINEERING, 2018, : 61 - 64
  • [7] Ensemble Machine Learning Models for Simulating the Missile Defense System
    Jin, Sihwa
    Dahouda, Mwamba Kasongo
    Joe, Inwhee
    DATA SCIENCE AND ALGORITHMS IN SYSTEMS, 2022, VOL 2, 2023, 597 : 142 - 156
  • [8] Experimental Comparison of Resampling Methods in a Multi-Agent System to Assist with Property Valuation
    Lasota, Tadeusz
    Luczak, Tomasz
    Trawinski, Bogdan
    AGENT AND MULTI-AGENT SYSTEMS: TECHNOLOGIES AND APPLICATIONS, 2011, 6682 : 342 - 352
  • [9] A hybrid of ensemble machine learning models with RFE and Boruta wrapper-based algorithms for flash flood susceptibility assessment
    Habibi, Alireza
    Delavar, Mahmoud Reza
    Sadeghian, Mohammad Sadegh
    Nazari, Borzoo
    Pirasteh, Saeid
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2023, 122
  • [10] Classification of hazelnut cultivars: comparison of DL4J and ensemble learning algorithms
    Koc, Caner
    Gerdan, Dilara
    Eminoglu, Maksut B.
    Yegul, Ugur
    Koc, Bulent
    Vatandas, Mustafa
    NOTULAE BOTANICAE HORTI AGROBOTANICI CLUJ-NAPOCA, 2020, 48 (04) : 2316 - 2327
12345