Discovering and orienting the edges connected to a target variable in a DAG via a sequential local learning approach
type: Item
instance of: scholarly article
title: Discovering and orienting the edges connected to a target variable in a DAG via a sequential local learning approach
zbMATH Open document ID: 1506.62184
author: Changzhang Wang
author: You Zhou
author: Qiang Zhao
author: Zhi Geng
published in: Computational Statistics and Data Analysis
publication date: 2018-11-23T00:00:00Z
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 6984024
zbMATH Keywords: causal network
zbMATH Keywords: directed acyclic graph
zbMATH Keywords: discover causes and effects
zbMATH Keywords: sequential structural learning
describes a project that uses: Hailfinder
describes a project that uses: TETRAD
MaRDI profile type: Publication
full work available at URL: j.csda.2014.03.003
OpenAlex ID: W2014887862
cites work: Local causal and Markov blanket induction for causal discovery and feature selection for classification. Part I: Algorithms and empirical evaluation
cites work: Tabu search-enhanced graphical models for classification in high dimensions
cites work: Adaptive probabilistic networks with hidden variables
cites work: Learning Bayesian networks: The combination of knowledge and statistical data
cites work: Q4217798
cites work: Q4382293
cites work: Q4496846
cites work: Q3096152
cites work: Towards scalable and data efficient learning of Markov boundaries
cites work: Causation, prediction, and search
cites work: The max-min hill-climbing Bayesian network structure learning algorithm
cites work: Q3096115
cites work: Decomposition of structural learning about directed acyclic graphs
DOI: 10.1016/J.CSDA.2014.03.003
description: scientific article; zbMATH DE number 6984024