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dc.contributor.authorIsarankura-Na-Ayudhya, Chartchalerm-
dc.contributor.authorNantasenamat, Chanin-
dc.contributor.authorPrachayasittikul, Virapong-
dc.contributor.authorPreeyanon, Likit-
dc.date.accessioned2011-12-02T10:00:40Z-
dc.date.available2011-12-02T10:00:40Z-
dc.date.issued2011-12-02-
dc.identifier.urihttp://hdl.handle.net/2003/29209-
dc.identifier.urihttp://dx.doi.org/10.17877/DE290R-3060-
dc.description.abstractPyBact is a software written in Python for bacterial identification. The code simulates the predefined behavior of bacterial species by generating a simulated data set based on the frequency table of biochemical tests from diagnostic microbiology textbook. The generated data was used for predictive model construction by machine learning approaches and results indicated that the classifiers could accurately predict its respective bacterial class with accuracy in excess of 99 %.en
dc.language.isoen-
dc.relation.ispartofseriesEXCLI Journal ; Vol. 10, 2011en
dc.subjectbacteriaen
dc.subjectbacterial identificationen
dc.subjectdata miningen
dc.subjectmicrobiologyen
dc.subjectPyBacten
dc.subjectPythonen
dc.subject.ddc610-
dc.titlePyBacten
dc.title.alternativean algorithm for bacterial identificationen
dc.typeText-
dc.type.publicationtypearticle-
dcterms.accessRightsopen access-
eldorado.dnb.zdberstkatid2132560-1-
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