Approximate conditional independence test using residuals

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抜粋

Conditional mutual information is a useful measure for detecting the association between variables that are also affected by other variables. Though permutation tests are used to check whether the conditional mutual information is zero to indicate mutual independence, permutations are difficult to perform because the other variables in a dataset may be associated with the variables in question. This problem is particularly acute when working with datasets of small sample size. This study aims to propose a computational method for approximating conditional mutual information based on the distribution of residuals in regression models. The proposed method can implement the permutation tests for statistical significance by translating the problem of measuring conditional independence into the problem of estimating simple independence. Additionally, a reliability of p-value in permutation test is defined to omit unreliably detected associations. We tested our proposed method's performance in inferring the network structure of an artificial gene network against comparable methods submitted to the Dream4 challenge.

元の言語英語
ホスト出版物のタイトルICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence
編集者Ana Rocha, Luc Steels, Jaap van den Herik
出版者SciTePress
ページ297-304
ページ数8
ISBN(電子版)9789897583957
出版物ステータス出版済み - 1 1 2020
イベント12th International Conference on Agents and Artificial Intelligence, ICAART 2020 - Valletta, マルタ
継続期間: 2 22 20202 24 2020

出版物シリーズ

名前ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence
2

会議

会議12th International Conference on Agents and Artificial Intelligence, ICAART 2020
マルタ
Valletta
期間2/22/202/24/20

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software

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  • これを引用

    Uda, S. (2020). Approximate conditional independence test using residuals. : A. Rocha, L. Steels, & J. van den Herik (版), ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence (pp. 297-304). (ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence; 巻数 2). SciTePress.