Grokbase Groups R r-help March 2002
FAQ
Hello,

I would like to test some learning algorithms (C5.0, or C4.5) using decision trees or neural network.

I didn't find anything in the R documentation for functions to apply on datasets (well, English is not my mother tongue and I have some problems to understand some functions descriptions). Does anybody know where I can find anything about that ?

Thank you very much,

Thomas

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  • Prof Brian D Ripley at Mar 10, 2002 at 3:45 pm

    On Sun, 10 Mar 2002, Thomas DEGRIS wrote:

    Hello,

    I would like to test some learning algorithms (C5.0, or C4.5) using
    decision trees or neural network.
    Those (C5 and C4.x) are proprietary algorithms, incompatible with the R
    licence.

    There is classification tree support in packages rpart and tree, and neural
    nets support in package nnet in the VR bundle.

    --
    Brian D. Ripley, ripley at stats.ox.ac.uk
    Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
    University of Oxford, Tel: +44 1865 272861 (self)
    1 South Parks Road, +44 1865 272860 (secr)
    Oxford OX1 3TG, UK Fax: +44 1865 272595

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  • Ggrothendieck at Mar 10, 2002 at 6:43 pm
    If your aim is to try out a large number of machine learning algorithms
    (as opposed to looking for the ones you mention specifically) you may
    find the free Weka package of interest:

    http://www.cs.waikato.ac.nz/~ml/weka/

    On 10 Mar 2002 at 15:54, Thomas DEGRIS wrote:

    I would like to test some learning algorithms (C5.0, or C4.5) using decision trees or neural network.
    -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
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  • Christian at Mar 11, 2002 at 6:52 am
    Hi,
    (IMHO) there is currently no package for C4.5/C5.0 in R.
    But you can use Rpart package which is very similar to CART ( Classification And Regression Tree - Breimann)

    ...and when anybody want use a really fast C4.5 and apriori algorithm - try:
    http://fuzzy.cs.uni-magdeburg.de/~borgelt/software.html


    ...i'm really surprised that currently no "Association-Rule" package is
    implemented in R, too and would share this intention to do with others ( for learning programming in R faster ).

    regards,
    Christian Schulz



    Am 10.03.2002 19:43:58, schrieb ggrothendieck at yifan.net:
    If your aim is to try out a large number of machine learning algorithms
    (as opposed to looking for the ones you mention specifically) you mayreally
    find the free Weka package of interest

    http://www.cs.waikato.ac.nz/~ml/weka/

    On 10 Mar 2002 at 15:54, Thomas DEGRIS wrote:

    I would like to test some learning algorithms (C5.0, or C4.5) using decision trees or neural network.
    -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
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  • Thomas at Mar 14, 2002 at 10:40 pm
    Hello,

    I thank people who helped me about the learning algorithms of R.
    I managed to use the "nnet" and "rpart" packages successfully [;-)] The
    thing is that I don't know which methods they use.
    Because I am writing a report on what I did with them, I'd like to know
    the actual names of these.
    I may appear stupid but I didn't find any known name in the documentation.

    Thank you very much.

    Thomas.



    Thomas DEGRIS wrote:
    Hello,

    I would like to test some learning algorithms (C5.0, or C4.5) using
    decision trees or neural network.
    I didn't find anything in the R documentation for functions to apply
    on datasets (well, English is not my mother tongue and I have some
    problems to understand some functions descriptions). Does anybody know
    where I can find anything about that ?

    Thank you very much,

    Thomas
    -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
    r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
    Send "info", "help", or "[un]subscribe"
    (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch
    _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
  • Prof Brian D Ripley at Mar 15, 2002 at 6:27 am

    On Thu, 14 Mar 2002, Thomas wrote:

    Hello,

    I thank people who helped me about the learning algorithms of R.
    I managed to use the "nnet" and "rpart" packages successfully [;-)] The
    thing is that I don't know which methods they use.
    Because I am writing a report on what I did with them, I'd like to know
    the actual names of these.
    I may appear stupid but I didn't find any known name in the documentation.
    `nnet' and `rpart'! They are just as much well-defined methods as
    `C4.5'. Why do you assume that Quinlan has an original method but
    Ripley/Therneau/Atkinson copy?
    Thank you very much.

    Thomas.



    Thomas DEGRIS wrote:
    Hello,

    I would like to test some learning algorithms (C5.0, or C4.5) using
    decision trees or neural network.
    I didn't find anything in the R documentation for functions to apply
    on datasets (well, English is not my mother tongue and I have some
    problems to understand some functions descriptions). Does anybody know
    where I can find anything about that ?

    Thank you very much,

    Thomas
    -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
    r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
    Send "info", "help", or "[un]subscribe"
    (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch
    _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
    --
    Brian D. Ripley, ripley at stats.ox.ac.uk
    Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
    University of Oxford, Tel: +44 1865 272861 (self)
    1 South Parks Road, +44 1865 272860 (secr)
    Oxford OX1 3TG, UK Fax: +44 1865 272595

    -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-
    r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
    Send "info", "help", or "[un]subscribe"
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  • Christian Schulz at Mar 15, 2002 at 4:32 pm
    thomas,
    download
    http://hesweb1.med.virginia.edu/biostat/s/techrep.pdf

    and you get a really nice introduction for Rpart and
    in Chapter 11 you find Relation to other porgramms .

    ...sometimes i compare the results between C4.5R8 and Rpart which
    are more or less the same, but i can interpret the results with Rpart
    better !
    regards,christian


    Thomas wrote:
    Hello,

    I thank people who helped me about the learning algorithms of R.
    I managed to use the "nnet" and "rpart" packages successfully [;-)]
    The thing is that I don't know which methods they use.
    Because I am writing a report on what I did with them, I'd like to
    know the actual names of these.
    I may appear stupid but I didn't find any known name in the
    documentation.

    Thank you very much.

    Thomas.



    Thomas DEGRIS wrote:
    Hello,

    I would like to test some learning algorithms (C5.0, or C4.5) using
    decision trees or neural network.
    I didn't find anything in the R documentation for functions to apply
    on datasets (well, English is not my mother tongue and I have some
    problems to understand some functions descriptions). Does anybody
    know where I can find anything about that ?

    Thank you very much,

    Thomas
    -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-

    r-help mailing list -- Read
    http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
    Send "info", "help", or "[un]subscribe"
    (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch
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    Christian Schulz
    MetaFacts GmbH

    Fon: +49 (0)30 69 51 71 - 0
    Fax: +49 (0)30 69 51 71 - 33
    mailto:c.schulz at metafacts.de
    http://www.metafacts.de





    --
    Mit freundlichen Gr??en


    Christian Schulz
    MetaFacts GmbH

    Fon: +49 (0)30 69 51 71 - 0
    Fax: +49 (0)30 69 51 71 - 33
    mailto:c.schulz at metafacts.de
    http://www.metafacts.de



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  • Thomas at Mar 22, 2002 at 2:58 pm
    Hello,

    I just wanted to thank you everybody who helped me with R. I finished
    for the moment to use it but we never know I may come back to it one day...


    So, thank you very much,

    All the best,


    Thomas



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