Hi, I have seen that R has a implementation of decision trees; however, after I have the tree with the classification: R Quinlan's trivial example of the "golf" decision tree. Outlook Temperature Humidity Windy PlayDontPlay 1 sunny 85 85 false DontPlay 2 sunny 80 90 true DontPlay 3 overcast 83 78 false Play 4 rain 70 96 false Play ... What's next? I mean, what is this information used for? or the goal is just to get this classification. I hope someone can help me and explain me, Thank you. Fátima [[alternative HTML version deleted]]
You get a model that enables you to predict future outcomes. Nice examples are available here: statmethods.net/advstats/cart.html ----------------Contact Details:------------------------------------------------------- Contact me: Tal.Galili@gmail.com | 972-52-7275845 Read me: talgalili.com (Hebrew) | biostatistics.co.il (Hebrew) | r-statistics.com (English) ---------------------------------------------------------------------------------------------- 2010/10/22 Fátima Caituiro-Monge <fatimac@gmail.com>> Hi, I have seen that R has a implementation of decision trees; however, > after I have the tree with the classification: > > R Quinlan's trivial example of the "golf" decision tree. > > Outlook Temperature Humidity Windy PlayDontPlay 1 sunny 85 85 false > DontPlay > 2 sunny 80 90 true DontPlay > 3 overcast 83 78 false Play > 4 rain 70 96 false Play > > ... > > What's next? I mean, what is this information used for? or the goal is just > to get this classification. > > I hope someone can help me and explain me, > > Thank you. > > > Fátima > > [[alternative HTML version deleted]] > > > ______________________________________________ > R-help@r-project.org mailing list > stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > >[[alternative HTML version deleted]]