데이터 마이닝을 이용한 주택가격 결정요인에 관한 연구

• 영문명: A Study on the Determinants of Housing Price Using Data Mining
• 발행기관: 한국주거환경학회
• 저자명: 전해정(Chun, Hae Jung)
• 간행물 정보: 『주거환경(한국주거환경학회논문집)』住居環境 제15권 제3호 (통권 제37호), 35~46쪽, 전체 12쪽
• 주제분류: 사회과학 > 지역개발
• 파일형태: PDF
• 발행일자: 2017.09.30

영문 초록

This study empirically analyzed the determinants of housing price using decision tree analysis, multiple regression analysis, and neural network analysis. The dependent variables are apartment real transaction price, independent variables are apartment size, apartment floor, construction year, city hall straight distance, 2 lane straight distance, 4 lane straight distance, subway station straight distance, Gangnam area, Gangseo area, urban area and Gangbuk area. As a result, the mean absolute error (MAE) of the neural network analysis is the smallest, and the linear correlation value shows the highest correlation between the real and predicted values. According to the decision tree analysis, the small size is divided into 70m2 instead of 59m2 , so it can be seen that the small and medium area is popular because 2-3 person households are popular. As a result of multiple regression analysis, apartment size, number of floors, 2 lane straight distance, and 4 lane straight distance were positively affected by housing price, while city hall straight distance, subway station straight distance, population density and region from Gangnam area to Gangseo area, Gangbuk area and urban area were negative.

목차

Ⅰ. 서 론

Ⅱ. 선행연구 고찰 및 이론고찰

Ⅲ. 데이터 마이닝

Ⅳ. 분석결과

Ⅴ. 결 론

키워드

주택가격 데이터 마이닝 의사결정나무분석 신경망분석 지리정보시스템 housing price data mining decision tree analysis neural network analysis geographic information system(GIS)