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==Summary== | |||
{{Information | |||
|Description='''Figure 1.''' a. Overview of experimental design. b. Examples of rules generated by rule mining algorithms grouped by type and ordered by decreasing complexity. c. A word cloud containing high frequency values in rules from the PART algorithm | |||
|Source={{cite journal |title=Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO) |journal=Journal of Biomedical Informatics |author=Panahiazar, M.; Dumontier, M.; Gevaert, O. |volume=72 |pages=8 |year=2017 |doi=10.1016/j.jbi.2017.06.017}} | |||
|Author=Panahiazar, M.; Dumontier, M.; Gevaert, O. | |||
|Date=2017 | |||
|Permission=[http://creativecommons.org/licenses/by-nc-nd/4.0/ Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International] | |||
}} | |||
== Licensing == | == Licensing == | ||
{{cc-by-nc-nd-4.0}} | {{cc-by-nc-nd-4.0}} |
Latest revision as of 19:02, 22 August 2017
Summary
Description |
Figure 1. a. Overview of experimental design. b. Examples of rules generated by rule mining algorithms grouped by type and ordered by decreasing complexity. c. A word cloud containing high frequency values in rules from the PART algorithm |
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Source |
Panahiazar, M.; Dumontier, M.; Gevaert, O. (2017). "Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO)". Journal of Biomedical Informatics 72: 8. doi:10.1016/j.jbi.2017.06.017. |
Date |
2017 |
Author |
Panahiazar, M.; Dumontier, M.; Gevaert, O. |
Permission (Reusing this file) |
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International |
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Licensing
|
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
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