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Using linear programming for weights identification of generalized bonferroni means in R
conference contribution
posted on 2012-01-01, 00:00 authored by Gleb BeliakovGleb Beliakov, Simon JamesSimon JamesThe generalized Bonferroni mean is able to capture some interaction effects between variables and model mandatory requirements. We present a number of weights identification algorithms we have developed in the R programming language in order to model data using the generalized Bonferroni mean subject to various preferences. We then compare its accuracy when fitting to the journal ranks dataset.
History
Event
Modeling Decisions for Artificial Intelligence. Conference (9th : 2012 : Catalonia, Spain)Source
Modeling decisions for artificial intelligence : 9th international conference, MDAI 2012, Girona, Catalonia, Spain, November 2012 : proceedingsSeries
Lecture Notes in Artificial Intelligence ; v.7647Pagination
35 - 44Publisher
SpringerLocation
Catalonia, SpainPlace of publication
Berlin, GermanyPublisher DOI
Start date
2012-11-21End date
2012-11-23ISSN
0302-9743ISBN-13
9783642346194Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2012, SpringerExtent
36Editor/Contributor(s)
V Torra, Y Narukawa, B Lopez, M VillaretTitle of proceedings
MDAI 2012 : Modeling decisions for artificial intelligence : 9th International Conference, Girona, Catalonia, Spain, November 2012 : proceedingsUsage metrics
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