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dc.contributor.authorBeckham, Christopher J.
dc.date.accessioned2015-11-23T00:58:36Z
dc.date.available2015-11-23T00:58:36Z
dc.date.issued2015-10
dc.identifier.citationBeckham, C.J. (2015). Classification and regression algorithms for WEKA implemented in Python. (Working paper 02/2015). Hamilton, New Zealand: University of Waikato, Department of Computer Science.en_NZ
dc.identifier.issn1177-777X
dc.identifier.urihttps://hdl.handle.net/10289/9773
dc.description.abstractWEKA is a popular machine learning workbench written in Java that allows users to easily classify, process, and explore data. There are many ways WEKA can be used: through the WEKA Explorer, users can visualise data, train classifiers and examine performance metrics; in the WEKA Experimenter, datasets and algorithms can be compared in an automated fashion; or, it can simply be invoked on the command-line or used as an external library in a Java project.en_NZ
dc.format.mimetypeapplication/pdf
dc.language.isoenen_NZ
dc.publisherUniversity of Waikato, Department of Computer Scienceen_NZ
dc.relation.ispartofseriesComputer Science Working Papersen_NZ
dc.rights© 2015 Christopher J. Beckhamen_NZ
dc.subjectComputer Scienceen_NZ
dc.titleClassification and regression algorithms for WEKA implemented in Pythonen_NZ
dc.typeWorking Paperen_NZ
uow.relation.series02/2015en_NZ


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