[R] Is there an ID3 implementation in R?

Tal Galili tal.galili at gmail.com
Tue Sep 2 18:11:46 CEST 2014


Dear Ista and Christian - this works wonderfully, thank you!




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On Tue, Sep 2, 2014 at 7:05 PM, Ista Zahn <istazahn at gmail.com> wrote:

> This is explained in the RWeka vignette, but briefly:
>
> ## load RWeka
> library(RWeka)
> ## look for a package providing id3
> WPM("refresh-cache")
> WPM("list-packages", "available") ## look for id3
> ## install package providing id3
> WPM("install-package", "simpleEducationalLearningSchemes")
> ## load the package
> WPM("load-package", "simpleEducationalLearningSchemes")
> ## make classifier
> ID3 <- make_Weka_classifier("weka/classifiers/trees/Id3")
> ## test it out.
> DF2 <- read.arff(system.file("arff", "contact-lenses.arff",
>                              package = "RWeka"))
> ID3(`contact-lenses` ~ ., data = DF2)
>
>
> Best,
> Ista
>
> On Tue, Sep 2, 2014 at 11:42 AM, Christian Schulz <chschulz at email.de>
> wrote:
> > Yes with: make_Weka_classifier(name, class = NULL, handlers = list(),
> init =
> > NULL)
> > HTH, Christian
> >
> >
> >
> >> Hi Wensui,
> >>
> >> When I looked at their docs:
> >> http://cran.r-project.org/web/packages/RWeka/RWeka.pdf
> >> It appeared they only have a connection to:
> >> J48
> >> LMT
> >> M5P
> >> DecisionStump
> >>
> >> Is it possible to connect it to:
> >> http://www.cs.tufts.edu/~ablumer/weka/doc/weka.classifiers.Id3.html
> >>
> >> If so, how?
> >>
> >> Thanks.
> >>
> >>
> >>
> >>
> >> ----------------Contact
> >> Details:-------------------------------------------------------
> >> Contact me: Tal.Galili at gmail.com |
> >> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew)
> |
> >> www.r-statistics.com (English)
> >>
> >>
> ----------------------------------------------------------------------------------------------
> >>
> >>
> >>
> >> On Tue, Sep 2, 2014 at 6:13 PM, Wensui Liu <liuwensui at gmail.com> wrote:
> >>
> >>> Rweka
> >>> On Sep 2, 2014 11:04 AM, "Tal Galili" <tal.galili at gmail.com> wrote:
> >>>
> >>>> Dear R help mailing list,
> >>>>
> >>>> I am looking for an ID3 implementation in R. I know that there are
> many
> >>>> other decision tree algorithms already implemented (via rpart, tree,
> >>>> caret,
> >>>> C50, etc., etc.), but for research purposes I would like to reproduce
> >>>> the
> >>>> result of running ID3.
> >>>>
> >>>> I was not able to find such an implementation when searching in any of
> >>>> the
> >>>> following:
> >>>> http://rseek.org/
> >>>> http://finzi.psych.upenn.edu/search.html
> >>>> http://cran.r-project.org/web/views/MachineLearning.html
> >>>>
> >>>> Any suggestions?
> >>>>
> >>>> Thanks,
> >>>> Tal
> >>>>
> >>>>
> >>>> ----------------Contact
> >>>> Details:-------------------------------------------------------
> >>>> Contact me: Tal.Galili at gmail.com |
> >>>> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il
> (Hebrew) |
> >>>> www.r-statistics.com (English)
> >>>>
> >>>>
> >>>>
> ----------------------------------------------------------------------------------------------
> >>>>
> >>>>          [[alternative HTML version deleted]]
> >>>>
> >>>> ______________________________________________
> >>>> R-help at r-project.org mailing list
> >>>> https://stat.ethz.ch/mailman/listinfo/r-help
> >>>> PLEASE do read the posting guide
> >>>> http://www.R-project.org/posting-guide.html
> >>>> and provide commented, minimal, self-contained, reproducible code.
> >>>>
> >>         [[alternative HTML version deleted]]
> >>
> >> ______________________________________________
> >> R-help at r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-help
> >> PLEASE do read the posting guide
> >> http://www.R-project.org/posting-guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
> >>
> >
> > ______________________________________________
> > R-help at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>

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