Optimization of Active Learning Strategies for Causal Network Structure

Optimization of Active Learning Strategies for Causal Network Structure

Causal structure learning is one of the major fields in causal inference. Only the Markov equivalence class (MEC) can be learned from observational data; to fully orient unoriented edges, experimental data need to be introduced from external intervention experiments to improve the identifiability of...

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Bibliographic Details
Main Authors: Mengxin Zhang, Xiaojun Zhang
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Mathematics
Subjects:
causal networks
structure learning
active learning
optimal design
Markov equivalence class
intervention
Online Access:https://www.mdpi.com/2227-7390/12/6/880

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https://www.mdpi.com/2227-7390/12/6/880

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