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Using R to preprocess data

Eibe Frank shows how the preprocessing tools implemented in R can be used to preprocess data before passing it on to Weka learning algorithms.

Tools implemented in R can preprocess data before passing it on to Weka learning algorithms. The Knowledge Flow’s RScriptExecutor component executes a user-supplied R script. Data can be loaded using an ArffLoader and passed to the RScriptExecutor, which is supplied with a script. Eibe demonstrates scripts that delete an attribute, produce a scatter plot matrix, and decompose the input into statistically independent components – after which the Naive Bayes classifier is run, and evaluated using cross-validation. R includes many other useful transformation methods. Detailed instructions are given in the accompanying download (these slides do not appear in the video itself).

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Advanced Data Mining with Weka

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