Comparison of different machine learning models for mass appraisal of real estate
Yükleniyor...
Tarih
2021
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Taylor & Francis
Erişim Hakkı
info:eu-repo/semantics/embargoedAccess
Özet
The present study aimed to compare five machine learning techniques, namely, artificial neural network (ANN), support vector machine (SVM), chi-square automatic interaction detection (CHAID), classification and regression tree (CART), and random forest (RF) for mass appraisal of real estate. Firstly, 1982 precedent data was collected throughout the entire study area for train and test models. Secondly, a total of 68 variables were considered for the mass appraisal. Subsequently, the five machine learning techniques were applied. Finally, the receiver operating characteristic (ROC) and various statistical methods were applied to compare five machine learning techniques.
Açıklama
Anahtar Kelimeler
Machine Learning, Mass Appraisal, Artificial Neural Network, Support Vector Machine, Chi-square Automatic Interaction Detection, Classification and Regression Tree, Random Forest
Kaynak
Survey Review
WoS Q Değeri
Q4
Scopus Q Değeri
Q2
Cilt
-
Sayı
-
