民間分譲マンションのモデルルーム来場者アンケートからの購買者の予測と分析

概要

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We propose the prediction models which tell who will really purchase an apartment from among those who visit a model room, and analyze the characteristic of purchase based on data-mining technique. The data of questionnaire collected from those who visited model rooms usually has a lot of missing values. In order to improve the precision of prediction, the original data is converted to the one and two dimensional probability data concerning purchase. This data conversion technique is applied to the data which an estate agent in Kansai owns. Decision-tree and logistic regression are applied in order to obtain prediction models. Precisions of three different data types: original categorical data, one dimensional probability data and two-dimensional one are compared. As a result of experiment, the followings are observed: 1. two dimensional probability data with logistic regression has the highest precision through different data, 2. customers having high purchase probability do not answer the questionnaire too much.
社団法人日本建築学会の論文
2006-08-30