기계학습을 통한 공동주택 가격결정요인 분석

• 영문명: Analysis for Factors Determining the Price of Multi-family Housing through Machine Learnings
• 발행기관: 한국주거환경학회
• 저자명: 김경민(Kim Gyeung Min)
• 간행물 정보: 『주거환경(한국주거환경학회논문집)』住居環境 제14권 제3호 (통권 제33호), 29~40쪽, 전체 12쪽
• 주제분류: 사회과학 > 지역개발
• 파일형태: PDF
• 발행일자: 2016.06.30

영문 초록

Recently machine learning algorithms begun Bigdata were blast incorporated into the AlphaGo apartments investment value of the Real Estate market forecast analysis. This has been an opportunity to increase the accuracy of the prediction. Such a prediction based on the accuracy of the analysis and cluster analysis logit analysis presents the major variables that affect the investment value determined through is significant on the point. Existing public housing research was concentrated on the macroscopic analysis. Through predictive analytics, machine learning algorithms have enabled the microscopic research combined with traditional statistical approaches. Machine learning algorithms for investment value of predictive analytics for Apartment Housing Price Determinants seen a person in the study was adopted. Based on the accuracy of these machine learning algorithms through C5.0, SVM, RF, K-means, logit analysis was conducted to determine the investment value factor analysis apartments. 3 May 2016 by the actual transaction data to the Bundang apartment investment decisions and investment determinants of cross sectional data were collected to analyze the data from the Ministry of Land and Real Estate Statistics Korea Appraisal Board. Column 17 and is composed of 220 data is Low. The column was composed of variable volumes per minute for apartments for rent and sale actual transaction size individual cases. 220 cases of the trading population was subjected to empirical analysis to the sample. It is significant to make predictive analytics a public housing developers, and take advantage of investors, end users, investment in real estate policy makers judged through machine learning.

목차

Abstract

Ⅰ. 서론

Ⅱ. 이론적 논의와 선행연구 검토

Ⅲ. 아파트 거래 특성 및 연구모형

Ⅳ. 실증분석

Ⅴ. 결론

참고문헌

키워드

기계학습 예측분석 공동주택 가격결정요인 투자가치 Machine Learning Predictive Analitics Multi-family Housing Factors Determining the Price Investment value