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Kernel-Trick Regression and Classification
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Huh, Myung-Hoe | - |
| dc.date.accessioned | 2021-09-04T18:30:46Z | - |
| dc.date.available | 2021-09-04T18:30:46Z | - |
| dc.date.created | 2021-06-15 | - |
| dc.date.issued | 2015-03 | - |
| dc.identifier.issn | 2287-7843 | - |
| dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/94194 | - |
| dc.description.abstract | Support vector machine (SVM) is a well known kernel-trick supervised learning tool. This study proposes a working scheme for kernel-trick regression and classification (KtRC) as a SVM alternative. KtRC fits the model on a number of random subsamples and selects the best model. Empirical examples and a simulation study indicate that KtRC's performance is comparable to SVM. | - |
| dc.language | English | - |
| dc.language.iso | en | - |
| dc.publisher | KOREAN STATISTICAL SOC | - |
| dc.title | Kernel-Trick Regression and Classification | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | Huh, Myung-Hoe | - |
| dc.identifier.doi | 10.5351/CSAM.2015.22.2.201 | - |
| dc.identifier.wosid | 000409437000008 | - |
| dc.identifier.bibliographicCitation | COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS, v.22, no.2, pp.201 - 207 | - |
| dc.relation.isPartOf | COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS | - |
| dc.citation.title | COMMUNICATIONS FOR STATISTICAL APPLICATIONS AND METHODS | - |
| dc.citation.volume | 22 | - |
| dc.citation.number | 2 | - |
| dc.citation.startPage | 201 | - |
| dc.citation.endPage | 207 | - |
| dc.type.rims | ART | - |
| dc.type.docType | Review | - |
| dc.identifier.kciid | ART001975499 | - |
| dc.description.journalClass | 2 | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.relation.journalResearchArea | Mathematics | - |
| dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
| dc.subject.keywordAuthor | Kernel trick | - |
| dc.subject.keywordAuthor | support vector machine | - |
| dc.subject.keywordAuthor | subsampling | - |
| dc.subject.keywordAuthor | cross-validation | - |
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