| Literature DB >> 28873918 |
Mamoru Iwabuchi1, Rumi Hirabayashi1, Kenryu Nakamura1, Nem Khan Dim2.
Abstract
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.Entities:
Keywords: URAWSS; dysgraphia; dyslexia; evaluation; machine learning
Mesh:
Year: 2017 PMID: 28873918
Source DB: PubMed Journal: Stud Health Technol Inform ISSN: 0926-9630