similar to: Logistic Regression - Interpreting SENS (Sensitivity) and SPEC (Specificity)

Dear Mr Peter Dalgaard and Mr Dieter Menne, I sincerely thank you for helping me out with my problem. The thing is taht I already have calculated SENS = Gg / (Gg + Bg) = 89.97% and SPEC = Bb / (Bb + Gb) = 74.38%. Now I have values of SENS and SPEC, which are absolute in nature. My question was how do I interpret these absolue values. How does these values help me to find out wheher my model is

Hi Hi I am working on credit scoring model using logistic regression. I havd main sample of 42500 clentes and based on their status as regards to defaulted / non - defaulted, I have genereted the probability of default. I have a hold out sample of 5000 clients. I have calculated (1) No of correctly classified goods Gg, (2) No of correcly classified Bads Bg and also (3) number of wrongly

Hi all, I have a problem to park the call with #700 when the SIP phone and the asterisk PBAX run on the same machine. Call parking works well if the SIP phone that I use is on a remote pc in comparison with the asterisk on the which it is registered. If the sipphone is in the same pc where asterisk is installed the command #700 doesn't work, and in the asterisk's CLI I can see no

>> I use this method with filtering unused in nested function args and local >> vars >> in my YAFL frontend (not finished :(( - at this moment generate LLVM >> bytecode but doesn't have all runtime suport code writed) > > So do you mean you pass static links for parent function stack frames as > arguments? How do you generate them? > Sorry, I must more

Hai, ? Im working on my dhcp server + dns setup with samba4.? ? i've exported the?keytabs ? samba-tool domain exportkeytab?/home/krb5.keytab.samba4 ? when i read the contents of this keytab ? ktutil rkt /home/krb5.keytab.samba4 list ?? 1??? 1???????????? RTD-DC1$@INTERNAL.DOMAIN.TLD ?? 2??? 1???????????? RTD-DC1$@INTERNAL.DOMAIN.TLD ?? 3??? 1???????????? RTD-DC1$@INTERNAL.DOMAIN.TLD ??

Dear List,   I am new to ROC analysis and the package ROCR. I want to compute the confidence intervals of sensitivity and specificity for a given cutoff value. I have used the following to calculate sensitivity and specificity:   data(ROCR.simple) pred <- prediction(ROCR.simple$predictions, ROCR.simple$labels)   se.sp <- function (cutoff, performance) {     sens <-

Hi, My questions concerns the ROCR package and I hope somebody here on the list can help - or point me to some better place. When evaluating a model's performane, like this: pred1 <- predict(model, ..., type="response") pred2 <- prediction(pred1, binary_classifier_vector) perf <- performance(pred, "sens", "spec") (Where "prediction" and

Dear Guru's, Is there a package (R of course) with programs for diagnostics - roc, sens , spec, kappa etc? Best wishes Fredrik L

I am running my code in a loop and it does not work but when I run it outside the loop I get the values I want. n <- 1000; # Sample size fitglm <- function(sigma,tau){ x <- rnorm(n,0,sigma) intercept <- 0 beta <- 0 ystar <- intercept+beta*x z <- rbinom(n,1,plogis(ystar)) xerr <- x + rnorm(n,0,tau) model<-glm(z ~ xerr, family=binomial(logit))

I have the following UPS that I'm trying to get to work with NUT: SU3000RTXL3U I have it connected via USB. My ups.conf looks like: [test] driver = usbhid-ups vendorid = 09ae port = auto When I run upsdrvctl -DD start, I get: Network UPS Tools - UPS driver controller 2.4.1 Starting UPS: test exec: /lib/nut/usbhid-ups -a test Network UPS Tools - Generic HID driver 0.34 (2.4.1)

Does zfs send maintain an internal state or lock? I attempted to restart a send that was interrupted when the sending system rebooted and the send hangs. Here''s the last few lines of the truss output: # zfs send -i tue live/fs at wed | ssh staging zfs receive -F -v tank/backup/fs at wed 6074: open("/dev/zfs", O_RDWR) = 3 6074: fstat64(3,

> As an optimization for shallow nested functions (e.g., 3 levels or less), > it seems to me you could just avoid the stack walking entirely and add > $k-1$ arguments to each function at level $k$, i.e., at most 2 arguments > in all. This may even be an easy first implementation. I use this method with filtering unused in nested function args and local vars in my YAFL frontend

On Nov 22, 2004, at 12:34 PM, Vladimir Merzliakov wrote: >> As an optimization for shallow nested functions (e.g., 3 levels or >> less), it seems to me you could just avoid the stack walking entirely >> and add $k-1$ arguments to each function at level $k$, i.e., at most >> 2 arguments in all. This may even be an easy first implementation. > > I use this method

Dear all, I have a standard method and two alternatives to perform a test, called method A and method B. I have calculated the sensitivity and specificity for standard method vs. method A and standard method vs. method B. Hence, I have two sensitivity values an two specificity values. To be clear, sensitivity and specificity was calculated from: Disease(A) No Disease(Ac) Total Positive

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]]

Hi, I have two sets of sensitivity, specificity, positive predictive value, and negative predictive value, and accuracy from two tests on the same subjects. Is there an R package that does such paired comparisons? Thanks, Gang Chen

Hi list, I'm new to R and I'm currently using ROCR package. Data in input look like this: DIAGNOSIS SCORE 1 0.387945 1 0.50405 1 0.435667 1 0.358057 1 0.583512 1 0.387945 1 0.531795 1 0.527148 0 0.526397 0 0.372935 1 0.861097 And I run the following simple code: d <- read.table("inputFile", header=TRUE); pred <- prediction(d$SCORE, d$DIAGNOSIS); perf <- performance(

Hi, Is there a way when doing logistic regression for the output to spit out accuracy, sensitivity, and specificity? I would like to know these basic measures for my model. Thanks! [[alternative HTML version deleted]]

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:

Hi, I'm relative new to R. I'm looking for a convenient way to calculate sensitivity and specificity in machine-learning models (SVM, ...). In a two-class case it's quite simple by calculating the TP, TN, FP, FN rates once but in the multi-class case I have to do it as often as there exist different classes (for each class). Of course I could do it manually in a for-loop or so. But is