Dear all,
the commented source code for the ROCR package
(http://cran.r-project.org/web/packages/ROCR) is now available on
github -- feel free to fork, add improvements, and contribute back!
https://github.com/ipa-tys/ROCR
Kind regards,
Tobias
___
R-
: "Tim Howard"
> Subject: [R] ROCR.plot methods, cross validation averaging
> To: , ,
>
> Message-ID: <4aba1079.6d16.00d...@gw.dec.state.ny.us>
> Content-Type: text/plain; charset=US-ASCII
>
> Dear R-help and ROCR developers (Tobias Sing and Oliver Sander)
gt;> Sent: Friday, September 18, 2009 11:00 AM
>> To: Greg Snow
>> Cc: Tobias Sing; r help
>> Subject: Re: [R] Writing Reports from R in Microsoft Office Open XML
>> format (follow-up)
>>
>>
>> I believe that their approach is based on DCOM a
ime to wrap it all up.
> There is also a Docbook-based version that uses
> R extensions to Docbook for authoring structured
> documents.
>
> D.
>
> Tobias Sing wrote:
>>
>> Dear all,
>>
>> has someone implemented functionality for writing reports from R in
&g
> Is the "probability of the true label" the best prediction to feed to
> the ROCR package, or is it better to use the "decision.value"
Since AFAIK they are related by a monotonous transformation, both
approaches should lead to the same ROC curve, shouldn't they? (not
tested)
On Tue, Aug 4, 2009
Waverley,
if you want to modify components of the ROCR plot, you need to direct
the parameters to the component functions by prefixing them with the
name of that component function. In your case, you should add
"boxplot.outline=FALSE" as follows:
plot(perf, avg= "vertical", spread.estimate="boxpl
Waverley, see help('performance-class') for a description of the slots.
Your AUCs will be in p...@y.values, which itself is a list (one list
element per run).
Thus, you can use functions like unlist or s/lapply to access them, e.g.
mean(unlist(p...@y.values))
Kind regards,
Tobias
On Sat, Jul
Waverley,
use @ (instead of $) to extract the slots from the performance object
(it's S4 class system).
HTH,
Tobias
On Sat, Jul 25, 2009 at 8:20 AM, Waverley wrote:
> I use ROCR to plot multiple runs' performance. Using the sample code
> as example:
>
> # plot ROC curves for several cross-val
Michael,
a lift chart for evaluating binary scoring classifiers, as I
understand it, plots...
lift score: P(Yhat = + | Y = +)/P(Yhat = +)
against
rate of rate of positive predictions: P(Yhat = +).
...across the continuum of possible cutoffs. If you want to do this,
here is how you would do this
Dear all,
has someone implemented functionality for writing reports from R in
Office Open XML format (*), similar to what odfWeave does for the ODF
format of OpenOffice? It would be great to have a kind of
"ooxmlWeave" at least for those of us who are forced to work in an
MS ecosystem.
(*) Of
t;,barcol=2)"
>
> Even I specify "barcol=2", the color of bars are still black, the default
> one, instead of red "2".
>
> --Tim
>
>
> --- On Tue, 5/12/09, Tobias Sing wrote:
>
> From: Tobias Sing
> Subject: Re: [R] ROCR: auc and logarithm
> 1. I have tried to understand how to extract area-under-curve value by
> looking at the ROCR document and googling. Still I am not sure if I am doing
> the right thing. Here is my code, is "auc1" the auc value?
> "
> pred1 <- prediction(resp1,label1)
>
> perf1 <- performance(pred1,"tpr","fpr")
To have several performance curves on a single plot, use the
"add=TRUE" option, e.g. as follows:
plot(perf1)
plot(perf2, add=TRUE, col='red')
Please read the help to ?plot.performance. It also tells you how you
can adjust all graphical parameters for the individual curves.
This slide deck contain
Regina,
to get a simple ROC curve, use the following sequence of commands:
pred <- prediction(predictions, labels)
perf <- performance(pred, "tpr", "fpr")
plot(perf)
In the first line, 'predictions' are the raw predictions (usually
numerical) of your classifier, and labels (as you correctly guesse
Waverley,
you can also use p...@y.values to access the slot (see
help(performance-class) for a description of the slots).
You might also want have a look at the code for demo(ROCR) and at this
slide deck:
http://rocr.bioinf.mpi-sb.mpg.de/ROCR_Talk_Tobias_Sing.ppt
HTH,
Tobias
On Sat, Feb 7, 20
Hi Stacey,
ROCR uses S4 classes. The elements are accessed using "@" instead of "$".
You can find an example on slide 12 of the following slide deck:
http://rocr.bioinf.mpi-sb.mpg.de/ROCR_Talk_Tobias_Sing.ppt
Also have a look at the R code that appears when you type "demo(ROCR)" in R
which contai
> plot(1,1, main=paste('Plot',i))
> }
> for example.
>
> Or, if you want ODFWeave to handle placement, then you need to
> break that into three separate plots.
>
> Sarah
>
>
>
>
> On Mon, Apr 14, 2008 at 2:20 PM, Tobias Sing <[EMAIL PROT
Dear all,
Max, first of all, many thanks for providing the odfWeave package.
My problem: Whenever I have multiple plots in one single chunk of my
ODF file, only the last plot gets shown. The problem can be reproduced
with this toy example (to be used in an ODF file together with
odfWeave -- I'm u
The are some papers on the topic (google for "roc surfaces"), but no R
packages for multi-class ROC analysis.
I personally have some doubts about the practical value of these
approaches in the case of more than two classes, but others may
disagree.
Kind regards,
Tobias
On Thu, Feb 21, 2008 at
On Feb 17, 2008 2:49 PM, Udo König <[EMAIL PROTECTED]> wrote:
> [...]
> Greg:
> To the odfWeave package: in [2] I found the sentence "The package is currently
> limited to creating text documents using OpenOffice". So it doesn´t seem work
> with MS-Word?
Udo,
I think odfWeave is exactly what you
Hadley,
On Feb 4, 2008 5:03 PM, hadley wickham <[EMAIL PROTECTED]> wrote:
> [...]
> Before Christmas I started working on a solution for this -
> http://crantastic.org - a site for searching, reviewing and tagging R
> packages. Unfortunately I've run out of steam lately (and the lack of
> a 64-bi
7, G Ilhamto <[EMAIL PROTECTED]> wrote:
> Dear R-helper,
>
> I am working with ROCR of Tobias Sing et. al. to compare the performances of
> logistic and nnet models on a binary response.
>
> I had the performance plots, but I have problem finding out other
> performance
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