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Symptom analysis of Parkinson disease using SVM-SMO and Ada-Boost classifiers

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bracu.degree.levelUndergraduate
bracu.type.groupStudent Works
datacite.rightsOpen Access
dc.contributor.advisorBiswas, Rubel
dc.contributor.advisorAlam, Md. Zahangir
dc.contributor.authorBillah, Muhtasim
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2014-02-17T05:18:18Z
dc.date.available2014-02-17T05:18:18Z
dc.date.copyright2014
dc.date.issued2014-01
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014.
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 46).
dc.description.degreeBachelor of Science in Computer Science and Engineering
dc.description.statementofresponsibilityMuhtasim Billah
dc.format.extent46 pages
dc.identifier.otherID 10101002
dc.identifier.urihttp://hdl.handle.net/10361/2938
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectData Miningen_US
dc.subjectParkinson dataen_US
dc.subjectClassification algorithmen_US
dc.subjectAssociation algorithmen_US
dc.subjectComputer science and engineering
dc.subjectWeka toolen_US
dc.titleSymptom analysis of Parkinson disease using SVM-SMO and Ada-Boost classifiersen_US
dc.typeThesisen_US

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Thesis (Bachelor of Science in Computer Science and Engineering)