Practical Approaches to Causal Relationship Exploration

  • Jiuyong Li
  • Lin Liu
  • Thuc Duy Le

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Table of contents

  1. Front Matter
    Pages i-x
  2. Jiuyong Li, Lin Liu, Thuc Duy Le
    Pages 1-7
  3. Jiuyong Li, Lin Liu, Thuc Duy Le
    Pages 9-21
  4. Jiuyong Li, Lin Liu, Thuc Duy Le
    Pages 23-32
  5. Jiuyong Li, Lin Liu, Thuc Duy Le
    Pages 33-50
  6. Jiuyong Li, Lin Liu, Thuc Duy Le
    Pages 51-66
  7. Jiuyong Li, Lin Liu, Thuc Duy Le
    Pages 67-72
  8. Back Matter
    Pages 73-80

About this book

Introduction

This brief presents four practical methods to effectively explore causal relationships, which are often used for explanation, prediction and decision making in medicine, epidemiology, biology, economics, physics and social sciences. The first two methods apply conditional independence tests for causal discovery. The last two methods employ association rule mining for efficient causal hypothesis generation, and a partial association test and retrospective cohort study for validating the hypotheses. All four methods are innovative and effective in identifying potential causal relationships around a given target, and each has its own strength and weakness. For each method, a software tool is provided along with examples demonstrating its use. Practical Approaches to Causal Relationship Exploration is designed for researchers and practitioners working in the areas of artificial intelligence, machine learning, data mining, and biomedical research. The material also benefits advanced students interested in causal relationship discovery.

Keywords

Bayesian networks Causal relationship Cohort study Local causal discovery Partial association

Authors and affiliations

  • Jiuyong Li
    • 1
  • Lin Liu
    • 2
  • Thuc Duy Le
    • 3
  1. 1.University of South AustraliaAdelaideAustralia
  2. 2.School of Information Technology and Mathematical SciencesUniversity of South AustraliaAdelaideAustralia
  3. 3.School of Information Technology and Mathematical SciencesUniversity of South AustraliaAdelaideAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-14433-7
  • Copyright Information The Author(s) 2015
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-14432-0
  • Online ISBN 978-3-319-14433-7
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • About this book
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