Journal of The Japanese Society for Quality Control
Online ISSN : 2432-1044
Print ISSN : 0386-8230
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Volume 53, Issue 1
Displaying 1-4 of 4 articles from this issue
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Invited Article
  • What is the Explainability of Machine Learning Models for Prediction Results ?
    Taku HARADA, Hiroyuki NISHIYAMA, Ryo HATANO
    Article type: Invited Article
    2023 Volume 53 Issue 1 Pages 4-9
    Published: January 15, 2023
    Released on J-STAGE: April 14, 2023
    DOIhttps://doi.org/10.20684/quality.53.1_4
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    　There is a growing need for machine learning technologies. In the past, the accuracy of the output results ( prediction results ) of machine learning models was the main focus of attention. Today, however, as machine learning technology is applied to various problem fields, it is required to explain not only the accuracy but also the basis on which the results were obtained. This is because machine learning models themselves are black boxes, and when data is input to a machine learning model, a certain output ( result ) is obtained, but it is difficult for users to understand why hat output ( result ) was obtained. For this background, a number of methods have been proposed to explain the basis of results obtained from machine learning models, and they are called “ eXplainable Artificial Intelligence：XAI ”. A variety of research is being conducted, from basic research to applied research. This paper introduces some of the explanation methods of XAI.
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Laboratory introduction
  • Activity of Sano Seminar in Tokyo University of Information Sciences and its Research profile
    Natsuki SANO
    Article type: Laboratory introduction
    2023 Volume 53 Issue 1 Pages 10-13
    Published: January 15, 2023
    Released on J-STAGE: April 14, 2023
    DOIhttps://doi.org/10.20684/quality.53.1_10
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    　In this article, we introduce the profile of the faculty of informatics, Tokyo University of Information Sciences （TUIS） and an education program in TUIS. And, we introduce an example of activity of SANO laboratory. SANO laboratory developed an education software of the Monty Hall problem for exhibition at school festival of TUIS and gathered about eighty people into our site and had them experience the software program. The developed software program can help intuitively understand the Monty Hall problem through dialogue interface and Monte Carlo simulation. In this article, we briefly summarize Monty Hall problem and the developed education software.
    　In addition, we introduce results of study concerning generation method of synthetic data by principal component analysis. We generated synthetic data from the anonymized data from a national survey of family income and expenditure in Japan by the proposed method and evaluated the utility and risk of the generated data.
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Overview of the Lecture
  • “ The essence and practice of KAIZEN and problem solving”
    ～ Why is problem solving not progressing in the workplace ～
    Takeo FURUYA
    Article type: Overview of the Lecture
    2023 Volume 53 Issue 1 Pages 14-19
    Published: January 15, 2023
    Released on J-STAGE: April 14, 2023
    DOIhttps://doi.org/10.20684/quality.53.1_14
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    　For many years, in addition to supporting various KAIZEN activities in companies ( manufacturing and service industries ), I have also provided practical support for problem solving for hospital doctors, prefectural government officials, NPO representatives, etc. In various situations, I found that most people did not have a basic understanding of problem solving. In addition, I found that there are common factors that prevent problem solving from proceeding well in all workplaces. In this paper, I clarified the factors that prevent problem solving from proceeding well, and summarized what I would like people who are working on problem solving to pay special attention to. I hope that problem solving will spread and permeate society and increase the international competitiveness of Japan.
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