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$case, namePos = 1)
>
> should also work and computes 80 performance measures.
>
> Best Matthias
>
> Am 25.10.22 um 06:42 schrieb Jin Li:
> > Hi Greg,
> >
> > This can be done by:
> > spm::pred.acc(testing$case, predict_testing)
> >
> > It will return both sensitivity and specificity, along with a few other
> > commonly used measures.
> >
> > Hope this helps,
> > Jin
> >
> > On Tue, Oct 25, 2022 at 6:01 AM Rui Barradas <ruipbarra...@sapo.pt>
> wrote:
> >
> >> 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 0.08127920
> >>>>
> >>>> # Sensitivity and Specificity
> >>>>
> >>>>
> >>>
> >>
> sensitivity<-(predict_testing[2,2]/(predict_testing[2,2]+predict_testing[2,1]))*100
> >>> Error in predict_testing[2, 2] : incorrect number of dimensions
> >>>> sensitivity
> >>> function (data, ...)
> >>> {
> >>> UseMethod("sensitivity")
> >>> }
> >>> <bytecode: 0x000002082a2f01d8>
> >>> <environment: namespace:caret>
> >>>>
> >>>>
> >>>
> >>
> specificity<-(predict_testing[1,1]/(predict_testing[1,1]+predict_testing[1,2]))*100
> >>> Error in predict_testing[1, 1] : incorrect number of dimensions
> >>>> specificity
> >>> function (data, ...)
> >>> {
> >>> UseMethod("specificity")
> >>> }
> >>> <bytecode: 0x000002082a2fa600>
> >>> <environment: namespace:caret>
> >>>
> >>> On Mon, Oct 24, 2022 at 10:45 AM Michael Dewey <
> li...@dewey.myzen.co.uk>
> >>> wrote:
> >>>
> >>>> 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 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$case,
> >>>>> p=0.7,
> >>>>> list=FALSE)
> >>>>> training <- data[ inTrain,]
> >>>>> testing <- data[-inTrain,]
> >>>>>
> >>>>> attach(training)
> >>>>> #model training and prediction
> >>>>> data_training <- glm(case ~ age+BMI+Calcium+Albumin+meno_1, data =
> >>>>> training, family = binomial(link="logit"))
> >>>>>
> >>>>> predict <- predict(data_training, data_predict = testing, type =
> >>>> "response")
> >>>>>
> >>>>> predict_testing <- ifelse(predict > 0.5,1,0)
> >>>>>
> >>>>> # Sensitivity and Specificity
> >>>>>
> >>>>>
> >>>>
> >>
>
> sensitivity<-(predict_testing[2,2]/(predict_testing[2,2]+predict_testing[2,1]))*100
> >>>>> sensitivity
> >>>>>
> >>>>>
> >>>>
> >>
>
> specificity<-(predict_testing[1,1]/(predict_testing[1,1]+predict_testing[1,2]))*100
> >>>>> specificity
> >>>>>
> >>>>> [[alternative HTML version deleted]]
> >>>>>
> >>>>> ______________________________________________
> >>>>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >>>>> https://stat.ethz.ch/mailman/listinfo/r-help
> >>>>> PLEASE do read the posting guide
> >>>> http://www.R-project.org/posting-guide.html
> >>>>> and provide commented, minimal, self-contained, reproducible code.
> >>>>>
> >>>>
> >>>> --
> >>>> Michael
> >>>> http://www.dewey.myzen.co.uk/home.html
> >>>>
> >>>
> >>> [[alternative HTML version deleted]]
> >>>
> >>> ______________________________________________
> >>> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >>> https://stat.ethz.ch/mailman/listinfo/r-help
> >>> PLEASE do read the posting guide
> >> http://www.R-project.org/posting-guide.html
> >>> and provide commented, minimal, self-contained, reproducible code.
> >>
> >> Hello,
> >>
> >> Instead of computing by hand, why not use package caret?
> >>
> >>
> >> tbl <- table(predict_testing, testing$case)
> >> caret::sensitivity(tbl)
> >> caret::specificity(tbl)
> >>
> >>
> >> Hope this helps,
> >>
> >> Rui Barradas
> >>
> >> ______________________________________________
> >> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> >> 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.
> >>
> >
> >
>
> --
> Prof. Dr. Matthias Kohl
> www.stamats.de
>
> ______________________________________________
> R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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@r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.
