Case Study:Constructing a Child-Support Decision Model from Screening Data

Abstract

In this paper, we report a case study of constructing a machine learning model from real data. The case report in this paper is to determine whether a child needs school support or not. This case study uses a Yamano-style screening sheet to determine the support for elementary school children. Conventionally, the decision on whether or not support is needed was made by a person. However, when the number of children increases, the amount of support exceeds the tractable amount. In addition, there was a problem that it was difficult to obtain a common standard of support-decision because of the total dependence of such decisions on local governments and schools. Therefore, a support-decision model was created by machine learning from screening data that were collected from the elementary schools. The procedures used to construct the model from real data, the accuracy of the model obtained, the lessons learned from the series of work, and future issues are presented.