Hi Micheal, Rui, Jin and Matthias,
I appreciate your time and help. The problem has been solved with your
guides.
Kind regards,
Greg.
On Tue, Oct 25, 2022 at 12:11 AM Prof. Dr. Matthias Kohl <
matthias.k...@stamats.de> wrote:
> MKclass::perfMeasures(predict_testing, truth = testing$case, namePos
MKclass::perfMeasures(predict_testing, truth = testing$case, namePos = 1)
should also work and computes 80 performance measures.
Best Matthias
Am 25.10.22 um 06:42 schrieb Jin Li:
Hi Greg,
This can be done by:
spm::pred.acc(testing$case, predict_testing)
It will return both sensitivity and
Hi Greg,
This can be done by:
spm::pred.acc(testing$case, predict_testing)
It will return both sensitivity and specificity, along with a few other
commonly used measures.
Hope this helps,
Jin
On Tue, Oct 25, 2022 at 6:01 AM Rui Barradas wrote:
> Às 16:50 de 24/10/2022, greg holly escreveu:
>
Às 16:50 de 24/10/2022, greg holly escreveu:
Hi Michael,
I appreciate your writing. Here are what I have after;
predict_testing <- ifelse(predict > 0.5,1,0)
head(predict)
1 2 3 5 7 8
0.29006984 0.28370507 0.10761993 0.02204224 0.12873872
THanks Michael for this.This is much appreciated. So, how can I estimate
the sensitivity and specificity after having the prediction on testing
data. Any thoughts?
Kind regards,
Greg
On Mon, Oct 24, 2022 at 12:10 PM Michael Dewey
wrote:
> So predict is a one-dimensional vector of predictions
So predict is a one-dimensional vector of predictions but you are
treating it as a two-dimensional matrix (presumably you think those are
the totals).
Michael
On 24/10/2022 16:50, greg holly wrote:
Hi Michael,
I appreciate your writing. Here are what I have after;
> predict_testing <- ifel
Rather hard to know without seeing what output you expected and what
error message you got if any but did you mean to summarise your variable
predict before doing anything with it?
Michael
On 24/10/2022 16:17, greg holly wrote:
Hi all R-Help ,
After partitioning my data to testing and traini
Hi Michael,
I appreciate your writing. Here are what I have after;
> predict_testing <- ifelse(predict > 0.5,1,0)
>
> head(predict)
1 2 3 5 7 8
0.29006984 0.28370507 0.10761993 0.02204224 0.12873872 0.08127920
>
> # Sensitivity and Specificity
Hi all R-Help ,
After partitioning my data to testing and training (please see below), I
need to estimate the Sensitivity and Specificity. I failed. It would be
appropriate to get your help.
Best regards,
Greg
inTrain <- createDataPartition(y=data$case,
p=0.7,
Try this:
> sens <- function(ct) { ct[2,2] / sum(ct[,2]) }
> spec <- function(ct) { ct[1,1] / sum(ct[,1]) }
>
>
> myt <- matrix( c(1427,271,110,166), ncol=2)
>
> sens(myt)
[1] 0.6014493
>
> spec(myt)
[1] 0.8404005
>
-Don
--
Don MacQueen
Lawrence Livermore National Laboratory
7000 East Ave
On Apr 25, 2014, at 10:58 AM, Si Qi L. wrote:
> Hi guys,
>
> I will be very grateful if you guys can do me a little favor on R. I am
> calculating the sensitivity and specificity for a 2*2 matrix, such as
>
> t
> 01
> 0 1427 110
> 1 271 166
>
>
>
> My codes are: sens <- func
Hi guys,
I will be very grateful if you guys can do me a little favor on R. I am
calculating the sensitivity and specificity for a 2*2 matrix, such as
t
01
0 1427 110
1 271 166
My codes are: sens <- function(ct) { ct[2,2] / sum(ct[,2]) }
spec <- f
On Thu, Aug 16, 2012 at 9:01 AM, Diana Marcela Martinez Ruiz
wrote:
> Hello,
>
> As obtained from a table svyglm clasificaion, sensitivity and specificity.
> The funtion ConfusionMatrix () of the library (caret)
> gives these results but not how to apply it to svyglm.
>
predict() will give you fi
Sensitivity and specificity are improper scoring rules so beware. They are
optimized by a bogus model.
Frank
Diana Marcela Martinez Ruiz wrote
>
> Hello,
>
> As obtained from a table svyglm clasificaion, sensitivity and
> specificity. The funtion ConfusionMatrix () of the library (caret)
> giv
Hello,
As obtained from a table svyglm clasificaion, sensitivity and specificity. The
funtion ConfusionMatrix () of the library (caret)
gives these results but not how to apply it to svyglm.
thanks
[[alternative HTML version deleted]]
_
r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
> On Behalf Of Jonathan Minton
> Sent: Monday, November 21, 2011 17:34
> To: r-help@r-project.org
> Subject: [R] Sensitivity and Specificity Forest Plots
>
> Dear R Users,
>
> Do you know of an existin
Dear R Users,
Do you know of an existing function that allows the production of
sensitivity and specificity forest plots?
See the following for an example:
http://www.google.co.uk/imgres?q=forest+plots+of+sensitivity+and+specificity&um=1&hl=en&authuser=0&biw=1920&bih=989&tbm=isch&tbnid=JLxXNU7iQ2N
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