dc.contributor.author | De War, Rhys | |
dc.contributor.author | Neal, Donna Liane | |
dc.date.accessioned | 2008-10-23T02:06:28Z | |
dc.date.available | 2008-10-23T02:06:28Z | |
dc.date.issued | 1994-07 | |
dc.identifier.citation | De War, R. & Neal, D.L. (1994). WEKA machine learning project: cow culling. (Working paper 94/12). Hamilton, New Zealand: University of Waikato, Department of Computer Science. | en_US |
dc.identifier.issn | 1170-487X | |
dc.identifier.uri | https://hdl.handle.net/10289/1141 | |
dc.description.abstract | This report describes an investigation into the application of machine learning tools in the area of agricultural database information. The Weka workbench is a set of machine learning software tools with a common data input and operation interface which has been developed by a research team at the University of Waikato, Department of Computer Science. An extract of a database containing information on dairy cows was processed by various tools in the Weka workbench over a three month period in early 1994. | en_US |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.relation.ispartofseries | Computer Science Working Papers | |
dc.subject | computer science | en_US |
dc.title | WEKA machine learning project: cow culling | en_US |
dc.type | Working Paper | en_US |
uow.relation.series | 94/12 | |