Human and Machine Learning Visible, Explainable, Trustworthy and Transparent

Human and Machine Learning Visible, Explainable, Trustworthy and Transparent / edited by Jianlong Zhou, Fang Chen.

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of “black-box” in ML methods, ML still needs to be interp...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Zhou, Jianlong (Editor), Chen, Fang (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2018.
Edition:1st ed. 2018.
Series:Human–Computer Interaction Series,
Springer eBook Collection.
Subjects:
User interfaces (Computer systems).
Artificial intelligence.
Pattern recognition.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • Part I Transparency in Machine Learning
  • Part II Visual Explanation of Machine Learning Process
  • Part III Algorithmic Explanation of Machine Learning Models
  • Part IV User Cognitive Responses in ML-Based Decision Making
  • Part V Human and Evaluation of Machine Learning
  • Part VI Domain Knowledge in Transparent Machine Learning Applications.

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