井上弥先生・樋口聡先生退職記念特集

INOUE, Wataru

Japanese

Hiroshima University Institutional Repository

広島大学学術情報リポジトリHiroshima University Institutional RepositoryTitle木と森からモデルの予測性と理解しやすさについて考える <随想>Author(s)井上, 弥Citation学習開発学研究 , 13 : 3 - 5Issue Date2021-03-30DOISelf DOI10.15027/50793URLhttps://ir.lib.hiroshima-u.ac.jp/00050793RightCopyright (c) 2021 広島大学大学院人間社会科学研究科学習開発学領域Relation      iPhone Face IDdeep learning   tree based model decision treeregression tree  Gini1 1R R Core Team, 2020 rpart Therneau & Atkinson, 2019 minsplit minbucket cp complexity parameter  100%R25 7interval scale , 1996R2  －　3　－    minsplit minbucket cp complexity parameter  random forest 1R R Core Team, 2020 h2o LeDell, Gill, Aiello, Fu, Candel, Click, & Kraljevic, 2020hidden layer   R R Core Team, 2020 randomForest Liaw & Wiener, 2002 ntree default 500mtryntree500    100%  －　4　－  Pepper 1942   tree forest         (1996).  , 67, 1-8. LeDell, E., Gill, N., Aiello, S., Fu, A., Candel, A., Click, C., Kraljevic, T., Nykodym, T., Aboyoun, P., Kurka, M., & Malohlava, M. (2020). h2o: R Interface for the 'H2O' Scalable Machine Learning Platform. R package version 3.32.0.1. https://CRAN.R-project.org/package=h2o Liaw, A. & Wiener, M. (2002). Classification and Regression by randomForest. R News 2(3), 18--22. Pepper, S. C. (1942). World hypotheses. University of California. R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/. Therneau, T. & Atkinson, B. (2019). rpart: Recursive partitioning and regression trees. R package version 4.1-15. https://CRAN.R-project.org/package=rpart    －　5　－

木と森からモデルの予測性と理解しやすさについて考える <随想>

https://ir.lib.hiroshima-u.ac.jp/files/public/5/50793/2021043014080044124/JEducSci_13_3.pdf

木と森からモデルの予測性と理解しやすさについて考える <随想>

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