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.