[R] Example Data Set(s) for nnet, rpart

Christian Schulz
Sun, 25 May 2003 12:00:41 -0000

...i  like the adult file, beacuse it is "real-life"
and have a lot of cases for good splitting
in train/test cases -  ok  you need more time, to train/test!

http://www.ics.uci.edu/~mlearn/MLSummary.html

Donated by Ron Kohavi
Predicting whether income exceeds $50K/yr based on census data
Documentation: On everything
48842 instances, 14 attributes (6 continuous and 8 nominal)
Missing attribute values
Originally listed as the "Census Income" Database. It was renamed
because it
is cited as the "Adult" database

regards,christian


----- Original Message -----
From: "Ko-Kang Kevin Wang" <kwan022 at stat.auckland.ac.nz>
To: "R Help" <r-help at stat.math.ethz.ch>
Sent: Sunday, May 25, 2003 10:15 AM
Subject: [R] Example Data Set(s) for nnet, rpart


> Hi,
>
> I'm doing a presentation on Neural Networks and Tree-Based Models in
two
> weeks, at the moment I'm looking for a data set to use in the
> presentation.  What I would like to use is a good old data, like the Iris
> data, that is already known by every statisticians.
>
> MASS4 uses the cpus data in Chapter 8.10 and the Cushing's syndrome in
> Chapter 12.4.  These two data sets plus the Iris data I have mentioned
> make three possible candidate data sets.  Does anyone has a good
> recommendation as to which data set is better?
>
> While I'm at it.  Is it technically correct to obtain (using
residuals())
> the residual sum of square from the nnet() and rpart() models.  Then say
> one is better than the other based on the statistic?
>
>
>
> --
> Cheers,
>
> Kevin
>
> --------------------------------------------------------------------------
----
> /* Time is the greatest teacher, unfortunately it kills its students */
>
> --
> Ko-Kang Kevin Wang
> Master of Science (MSc) Student
> SLC Tutor and Lab Demonstrator
> Department of Statistics
> University of Auckland
> New Zealand
> Homepage: http://www.stat.auckland.ac.nz/~kwan022
> Ph: 373-7599
>     x88475 (City)
>     x88480 (Tamaki)
>
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