Data mining in real estate appraisal: a model tree and multivariate adaptive regression spline approach

Acciani, Claudio; Fucilli, Vincenzo; Sardaro, Ruggiero

doi:10.13128/aestimum-9560

Cited by 3 publications

(1 citation statement)

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“…Theo hướng nghiên cứu trên, Claudio Acciani và cộng sự [5] đã sử dụng mô hình cây xác định các yếu tố tác động đến giá nông trại tại Ý. Các yếu tố khoảng cách đến thị trấn, diện tích, sự thuận lợi về giao thông, điện nước được xây dựng để đưa vào mô hình. Mingchin Chen và cộng sự [6] đã sử dụng cây quyết định để đánh giá mức độ quan trọng của các yếu tố tác động đến giá nhà tại Đài Loan.…”

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Application of Decision Tree Model in Mass Land Valuation: A Case Study in Vung Tau City

Huu Cuong

2022

EES

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Land valuation is one of many important tasks in land use and management. In order to be objective and scientific in land valuation, it is necessary to identify factors affecting land price and quantify the relationship between land feature factors and land value. The goal of the study is to apply the decision-tree regression model to build mass land pricing models in Vung Tau city. The decision-tree regression model is applied in land valuation by determining the relationship between a combination of land feature factors and corresponding averaged land price. Research on building the land pricing model with independent variables includes business density, area, road types, business activities and road width based on 883 survey samples. The final result of this tree model was categorized into 51 divided groups, and pruned trees included 15 divided groups. The importance of the independent variables, namely, business density, region, road level, business activities and road width are 100%, 83.48%, 78.87%, 58.78% and 10.03% respectively. The interpretation rate of the independent variables to the formation of land price model is 86%. The decision-tree regression model suggests another approach to land valuation theory.

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Section: Mở đầU *unclassified

Application of Decision Tree Model in Mass Land Valuation: A Case Study in Vung Tau City

Huu Cuong

2022

EES

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A roadmap to determine the important factors of the house value: a case study by using actual price registration data of Taipei housing transactions

Wang

Chen

2018

Ind. Jour. Manag. & Prod.

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While many studies have applied data mining techniques to judge housing prices, few have decoded the important attributes or prioritized them simultaneously. This paper aims to utilize five data mining techniques to discover the important attributes for three major types of real estate in Taipei city. The datasets, involving a total of 22,480 transactions, were publicly available from the Taiwan Actual Price Registration from July 2013 to August 2015. The five models are decision trees, random forests, model trees, artificial neural networks and multiple regression. The criteria used to measure the forecasting accuracy are MAPE, R², RMSE, MAE and COR. The model with the best performance for all houses is the Model Tree with a MAPE value of 27.59. As for apartments, the best is Random Forests. Artificial Neural Networks perform best for suites and buildings with elevators. Different housing types need different models. Furthermore, the attributes importance helps us to conclude the really critical attributes, which include the floor area, administrative districts, parking area and land area, and their rankings. This variable ranking and selection procedure proposed by this research can also be adopted to improve the prediction efficiency for most big data applications other than the housing transactions.

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Evaluation of Classification and Ensemble Algorithms for Bank Customer Marketing Response Prediction

Apampa¹

2016

Journal of International Technology and Information Management

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Data mining in real estate appraisal: a model tree and multivariate adaptive regression spline approach

Cited by 3 publications

References 0 publications

Application of Decision Tree Model in Mass Land Valuation: A Case Study in Vung Tau City

Application of Decision Tree Model in Mass Land Valuation: A Case Study in Vung Tau City

A roadmap to determine the important factors of the house value: a case study by using actual price registration data of Taipei housing transactions

Evaluation of Classification and Ensemble Algorithms for Bank Customer Marketing Response Prediction

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