Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/429362
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dc.coverage.spatialAnalyse state-of-the-art models for regression and classification-based learning challenges
dc.date.accessioned2022-12-21T10:10:16Z-
dc.date.available2022-12-21T10:10:16Z-
dc.identifier.urihttp://hdl.handle.net/10603/429362-
dc.format.extentxxxii, 248
dc.languageEnglish
dc.relation161
dc.rightsuniversity
dc.titleEnhancement of parallel and non parallel twin hyperplane based learning methods using robust loss functions
dc.title.alternative
dc.creator.researcherGupta, Umesh
dc.subject.keywordArtificial Intelligence
dc.subject.keywordExtreme Learning Machine
dc.subject.keywordMachine Learning
dc.subject.keywordSupport Vector Machine
dc.description.note
dc.contributor.guideGupta, Deepak
dc.publisher.placeJote
dc.publisher.universityNational Institute of Technology Arunachal Pradesh
dc.publisher.institutionDepartment of Computer Science and Engineering
dc.date.registered2017
dc.date.completed2022
dc.date.awarded2022
dc.format.dimensions30cm
dc.format.accompanyingmaterialNone
dc.source.universityUniversity
dc.type.degreePh.D.
Appears in Departments:Department of Computer Science and Engineering

Files in This Item:
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01_title.pdfAttached File119.64 kBAdobe PDFView/Open
02_prelim pages.pdf339.8 kBAdobe PDFView/Open
03_content.pdf163.93 kBAdobe PDFView/Open
04_abstract.pdf93.48 kBAdobe PDFView/Open
05_chapter 1.pdf309.99 kBAdobe PDFView/Open
06_chapter 2.pdf575.74 kBAdobe PDFView/Open
07_chapter 3.pdf625.79 kBAdobe PDFView/Open
08_chapter 4.pdf1.02 MBAdobe PDFView/Open
09_chapter 5.pdf1.33 MBAdobe PDFView/Open
10_annexures.pdf251.77 kBAdobe PDFView/Open
11_chapter 6.pdf1.2 MBAdobe PDFView/Open
12_chapter 7.pdf574.89 kBAdobe PDFView/Open
13_chapter 8.pdf967.08 kBAdobe PDFView/Open
14_chapter 9.pdf1.15 MBAdobe PDFView/Open
80_recommendation.pdf196.96 kBAdobe PDFView/Open


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