Machine Learning Based Evaluation of Reading and Writing Difficulties

Mamoru Iwabuchi, Rumi Hirabayashi, Kenryu Nakamura, Nem Khan Dim

研究成果: Conference contribution

2 引用 (Scopus)

抜粋

The possibility of auto evaluation of reading and writing difficulties was investigated using non-parametric machine learning (ML) regression technique for URAWSS (Understanding Reading and Writing Skills of Schoolchildren) [1] test data of 168 children of grade 1-9. The result showed that the ML had better prediction than the ordinary rule-based decision.

元の言語English
ホスト出版物のタイトルHarnessing the Power of Technology to Improve Lives
編集者Peter Cudd, Luc de Witte
出版者IOS Press
ページ1001-1004
ページ数4
ISBN(電子版)9781614997979
DOI
出版物ステータスPublished - 2017 1 1
外部発表Yes

出版物シリーズ

名前Studies in Health Technology and Informatics
242
ISSN(印刷物)0926-9630
ISSN(電子版)1879-8365

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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  • これを引用

    Iwabuchi, M., Hirabayashi, R., Nakamura, K., & Dim, N. K. (2017). Machine Learning Based Evaluation of Reading and Writing Difficulties. : P. Cudd, & L. de Witte (版), Harnessing the Power of Technology to Improve Lives (pp. 1001-1004). (Studies in Health Technology and Informatics; 巻数 242). IOS Press. https://doi.org/10.3233/978-1-61499-798-6-1001