Abstract
Network models can be classified into two large groups: undirected and directed. Directed network graphs that can represent causal relationships are likely more appropriate in bio-medical data. There have been many studies to estimate DAGs(Directed Acyclic Graphs), of which the two-stage approach using lasso effectively. Find the edges between the nodes in the first step and find the direction in the second step. In this paper, we try to compare which penalized regression is better to find neighborhoods through simulations. We present the result of the simulations that shows which penalized regression is the best.
Original language | English |
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Title of host publication | ICUFN 2018 - 10th International Conference on Ubiquitous and Future Networks |
Publisher | IEEE Computer Society |
Pages | 18-21 |
Number of pages | 4 |
ISBN (Print) | 9781538646465 |
DOIs | |
Publication status | Published - 2018 Aug 14 |
Event | 10th International Conference on Ubiquitous and Future Networks, ICUFN 2018 - Prague, Czech Republic Duration: 2018 Jul 3 → 2018 Jul 6 |
Publication series
Name | International Conference on Ubiquitous and Future Networks, ICUFN |
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Volume | 2018-July |
ISSN (Print) | 2165-8528 |
ISSN (Electronic) | 2165-8536 |
Other
Other | 10th International Conference on Ubiquitous and Future Networks, ICUFN 2018 |
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Country/Territory | Czech Republic |
City | Prague |
Period | 18/7/3 → 18/7/6 |
Bibliographical note
Publisher Copyright:© 2018 IEEE.
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture