Date(s) - 29/01/2013
3:30 pm - 5:00 pm
Category(ies) No Categories
Weka is a collection of machine learning algorithms for data mining tasks. For example, in a previous seminar Dr. Matt Davies used it to find metabolites that predict disease in twins. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
I’ll be doing a walk through of the Graphical User Interface version as think users will find this most easy to access, rather than the command line java calls. I’ll be running through the Explorer point and clicks and also focusing on the Experimenter that allows you to line up a whole load of methods and then run them and statistically benchmark them against each.
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