Tanagra's father is also a fan of R. It may seem strange and / or contradictory. But really, I'm mostly a big fan of data mining. And the software is an essential component. I spend so much time to dissect, evaluate their behavior in response to data, and analyze their source code where possible, in short, to study them in all seams. This work fascinates me altogether. I have always done. With the Internet, I can share the fruit of my reflections with others.
In this tutorial, we present the package to rattle R specializes in Data Mining. It does not include new methods of learning, but rather to add a graphical user interface (GUI in English, "graphical user interface") to R. Thus, a physician, unaware of the programming language R, will nevertheless drive its analysis by simply clicking on menus or buttons, just like the way "Explorer" software Weka. Nothing too revolutionary, then, but oh so important for novice users who want to go to basics: process their data using R without having to invest in learning the tedious programming.
To describe the operation of Rattle, we use the frame of the white paper published by its author in the Journal of R (see reference). We will achieve the following sequence of operations: load the file, split it into learning samples and testing, define the role of variables (target vs. Predictors) make some descriptive statistics and graphs to understand the data, build models predictors on the training sample, the gauge on the test sample through the usual tools of assessment (confusion matrix, a few curves).
Tags Key : R software, rpart, random forest, glm, decision trees, logistic regression, random forests, random forests
Link: fr_Tanagra_Rattle_Package_for_R.pdf
Data : heart_for_rattle.txt
References :
Togaware, "Rattle "
CRAN, "Rattle Package - Graphical user interface for data mining in R "
GJ Williams, " Rattle: A GUI for Data Mining R", R in The Journal Vol. 1 / 2, pages 45-55, december 2009.
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