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Online Markov Blanket Discovery With Streaming Features
2020 IEEE International Conference on Knowledge Graph (ICKG), 2020The Markov blanket (MB) in Bayesian networks has attracted much attention since the MB of a target attribute (T) is the minimal feature subset with maximum prediction ability for classification. Nevertheless, traditional MB discovery methods such as IAMB, HITON-MB, and MMMB are not suitable for streaming features.
Dianlong You +5 more
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Markov blanket and Markov boundary of multiple variables
J. Mach. Learn. Res., 2018Summary: Markov blanket (Mb) and Markov boundary (MB) are two key concepts in Bayesian networks (BNs). In this paper, we study the problem of Mb and MB for multiple variables. First, we show that Mb possesses the additivity property under the local intersection assumption, that is, an Mb of multiple targets can be constructed by simply taking the union
Xu-Qing Liu, Xin-sheng Liu
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Markov blankets: Realism and our ontological commitments
Behavioral and Brain Sciences, 2022Abstract The authors argue that their target is orthogonal to the realism and instrumentalist debate. I argue that it is born directly from it. While the distinction is helpful in illuminating how some ontological commitments demand a theory of implementation, it's less clear whether different views cleanly map onto the epistemic and metaphysical ...
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Local Learning Algorithm for Markov Blanket Discovery
2007Learning of Markov blanket can be regarded as an optimal solution to the feature selection problem. In this paper, we propose a local learning algorithm, called Breadth-First search of MB (BFMB), to induce Markov blanket (MB) without having to learn a Bayesian network first. It is demonstrated as (1) easy to understand and prove to be sound in theory; (
Shunkai Fu, Michel C. Desmarais
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Selecting Features by Learning Markov Blankets
2007In this paper I propose a novel feature selection technique based on Bayesian networks. The main idea is to exploit the conditional independencies entailed by Bayesian networks in order to discard features that are not directly relevant for classification tasks.
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Markov Blanket Approximation Based on Clustering
2011This paper presents new idea for Markov blanket approximation. It uses well known heuristic ordering of variables based on mutual information, but in another way then it was considered in previous works. Instead of using it as a simple help tool in a more complicated method most often based on statistical tests - presented here idea tries to rely ...
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A Fast Markov blanket discovery algorithm
2014 IEEE 5th International Conference on Software Engineering and Service Science, 2014Learning Markov blanket MB plays an important role in feature selection for classification, causal discovery, and Bayesian Networks learning. In this paper, an efficient and effective algorithm, called Fast Iterative Parent-Child based search of MB (FIPC-MB) is proposed to learn the MB of the target variable T.
Xiaofeng Zhu, Youlong Yang
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Identifying Markov Blankets Using Lasso Estimation
2004Determining the causal relation among attributes in a domain is a key task in data mining and knowledge discovery. The Minimum Message Length (MML) principle has demonstrated its ability in discovering linear causal models from training data. To explore the ways to improve efficiency, this paper proposes a novel Markov Blanket identification algorithm ...
Gang Li 0009 +2 more
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Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm
Interdisciplinary Sciences Computational Life Sciences, 2021Wei Liu +6 more
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Ordinal causal discovery based on Markov blankets
Computational StatisticszbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yu Du, Yi Sun, Luyao Tan
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