A DISCUSSION OF SOFTWARE CHOICES IN TEACHING OF<br>DATA MINING TECHNIQUES


Authors: 
Siva Ganesh
Pages: 
online
Year: 
2008
Publisher: 
Proceedings from the 6TH AUSTRALIAN CONFERENCE ON TEACHING STATISTICS (OZCOTS)
URL: 
http://silmaril.math.sci.qut.edu.au/ozcots2008/OZCOTS-08-Proceedings.pdf
Abstract: 

Many tertiary institutions now include 'Data Mining' as a topic in their Statistics curriculum,<br>both at undergraduate and postgraduate levels. The choice of software for learning the topic of<br>Data Mining is an interesting issue to think about. There is a wide range of such software<br>available, from commercially popular ones such as SAS/Enterprise Miner, Statistica/Data Miner<br>and S-plus/Insightful Miner to free ones such as R and Weka. The main aim of this paper is to<br>discuss the pros and cons of such software, including their capabilities to handle and manipulate<br>large volumes data, all from a teaching/learning point of view at both introductory and more<br>advanced levels.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education

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