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dc.contributor.authorCunningham, Sally Jo
dc.date.accessioned2008-10-20T22:54:28Z
dc.date.available2008-10-20T22:54:28Z
dc.date.issued1995-04
dc.identifier.citationCunningham, S. J. (1995). Machine learning and statistics: a matter of perspective. (Working paper 95/11). Hamilton, New Zealand: University of Waikato, Department of Computer Science.en_US
dc.identifier.issn1170-487X
dc.identifier.urihttps://hdl.handle.net/10289/1089
dc.description.abstractInformation has become an important commercial commodity-indeed, possibly the most important product of the future. While we have well-developed technologies to store data, the analysis to extract information is time-consuming and requires skilled human intervention. Machine learning algorithms augment statistical analysis by providing mechanisms that automate the information discovery process. These algorithms also tend to be more accessible to end-users and domain experts. The two analysis methods are converging, and the fields have much to offer each other.en_US
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherUniversity of Waikato, Department of Computer Scienceen_US
dc.relation.ispartofseriesComputer Science Working Papers
dc.subjectcomputer scienceen_US
dc.titleMachine learning and statistics: a matter of perspectiveen_US
dc.typeWorking Paperen_US
uow.relation.series95/11


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