Togaware DATA MINING
Desktop Survival Guide
by Graham Williams
Google


Moving into R

R is a statistical programming language together with an extensive collection of packages (of which Rattle is one) that provide a comprehensive toolkit for, amongst other things, data mining. Indeed, R is extensively deployed in bio-informatics, epidemiology, geophysics, agriculture and crop science, ecology, oceanography, fisheries, risk analysis, process engineering, pharmaceutical research, customer analytics, sociology, political science, psychology, and more.

One of the goals of Rattle is to ease a user's transition into using R directly, and thereby unleashing the full power of the language. R is a relatively simple language to learn, but has its own idiosyncrasies that emerge in any language that has such a long history, as R does.

In this chapter we discuss how we can access the internal data structures used by Rattle. This then allows us to smoothly switch between using Rattle and R in a single session. We significantly augment the functionality encapsulated in Rattle through this direct interaction with R, whilst not losing the ability to quickly explore the results in Rattle.



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