Hi. Thnx a lot. I will try that.
nitin On 1/24/07, Tobias Sing <[EMAIL PROTECTED]> wrote: > > Maybe ROCR might help you. > You can visualize the prec/rec-trade-off across the range of all cutoffs: > assuming your numerical predictions are in scores and the true class > labels are in classes: > pred <- prediction( scores, classes ) > perf <- performance(pred, 'rec','prec') > plot(perf) > > HTH, > Tobias > > On 1/24/07, nitin jindal <[EMAIL PROTECTED]> wrote: > > Hi, > > > > I am using logistic regression model named lrm(Design) > > > > Rite now I was using Area Under Curve (AUC) for testing my model. But, > now I > > have to calculate precision/recall of the model on test cases. > > For lrm, precision and recal would be simply defined with the help of 2 > > terms below: > > True Positive (TP) - Number of test cases where class 1 is given > probability > > >= 0.5. > > False Negative (FP) - Number of test cases where class 0 is given > > probability >= 0.5. > > > > Precision = TP / (TP + FP) > > Recall = TP / ( Number of Positive Samples in test data) > > > > Any help is appreciated. > > > > I an write a long code with for loops and all, but is there any inbuild > > function or just few commands that would do the task. > > > > regards, > > Nitin > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > [email protected] mailing list > > 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. > > > > > -- > Tobias Sing > Computational Biology and Applied Algorithmics > Max Planck Institute for Informatics > Saarbrucken, Germany > Phone: +49 681 9325 315 > Fax: +49 681 9325 399 > http://www.tobiassing.net > [[alternative HTML version deleted]] ______________________________________________ [email protected] mailing list 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.
