A tutorial on learning causal influence

Richard E. Neapolitan*, Xia Jiang

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingChapter

    Abstract

    In the 1990's related research in artificial intelligence, cognitive science, and philosophy resulted in a method for learning causal relationships from passive data when we have data on at least four variables. We illustrate the method using a few simple examples. Then we present recent research showing that we can even learn something about causal relationships when we have data on only two variables.

    Original languageEnglish (US)
    Title of host publicationInnovations in Machine Learning
    Subtitle of host publicationTheory and Applications
    EditorsDawn Holmes, Lakhmi Jain
    Pages29-71
    Number of pages43
    DOIs
    StatePublished - Dec 11 2006

    Publication series

    NameStudies in Fuzziness and Soft Computing
    Volume194
    ISSN (Print)1434-9922

    ASJC Scopus subject areas

    • Computer Science (miscellaneous)
    • Computational Mathematics

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