Optimization plugin for RapidMiner
| dc.contributor.author | Umaashankar, Venkatesh | |
| dc.contributor.author | Sangkyun, Lee | |
| dc.date.accessioned | 2018-10-12T09:12:51Z | |
| dc.date.available | 2018-10-12T09:12:51Z | |
| dc.date.issued | 2012-04 | |
| dc.description.abstract | Optimization in general means selecting a best choice out of various alternatives, which reduces the cost or disadvantage of an objective. Optimization problems are very popular in the fields such as economics, finance, logistics, etc. Optimization is a science of its own and machine learning or data mining is a diverse growing field which applies techniques from various other areas to find useful insights from data. Many of the machine learning problems can be modelled and solved as optimization problems, which means optimization already provides a set of well established methods and algorithms to solve machine learning problems. Due to the importance of optimization in machine learning, in recent times, machine learning researchers are contributing remarkable improvements in the field of optimization. We implement several popular optimization strategies and algorithms as a plugin for RapidMiner, which adds an optimization tool kit to the list of existing arsenal of operators in RapidMiner. | en |
| dc.identifier.uri | http://hdl.handle.net/2003/37183 | |
| dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-19179 | |
| dc.language.iso | en | de |
| dc.relation.ispartofseries | Technical report / Sonderforschungsbereich Verfügbarkeit von Information durch Analyse unter Ressourcenbeschränkung;4/2012 | |
| dc.subject.ddc | 004 | |
| dc.title | Optimization plugin for RapidMiner | en |
| dc.type | Text | de |
| dc.type.publicationtype | report | de |
| dcterms.accessRights | open access | |
| eldorado.secondarypublication | false | de |