セノグチ　　ジュンスケ   瀬之口　潤輔    所属   コンピュータサイエンス学部 コンピュータサイエンス学科    職種   教授
言語種別	英語
発行・発表の年月	2021/09
形態種別	学術論文
査読	査読あり
標題	Forecast of complex financial big data using model tree optimized by bilevel evolution strategy
執筆形態	単著
掲載誌名	Journal of Big Data
掲載区分	国外
出版社・発行元	Journal of Big Data
著者・共著者	Junsuke Senoguchi
概要	In order to avoid overfitting with a pattern recognition model, it is necessary to remove in advance the extraordinary values that deviate significantly from the true pattern of the population. In this study, the sample space was divided into a highly versatile space and a low versatility space by using the globally optimal decision tree. Then, the space with a low evaluation value was defined as the space with relatively large noise, and the pattern recognition model was created except for the data that belongs to the space with relatively large noise.