Displaying 2 results from an estimated 2 matches for "validationdata".
2009 Jul 17
2
Getting the C-index for a dataset that was not used to generate the logistic model
...del, and the other for evaluating it. The structure
is as follows:
column headers are "got a loan" (dichotomous), "hourly income" (continuous),
and "owns own home" (dichotomous)
The training data is
*trainingData[1,] = c(0,12,0)*
*...*
etc
and the validation data is
*validationData[1,] = c(1,35,1)*
*...*
etc
I use Prof. Harrell's excellent Design modules to perform a logistic
regression on the training data like so:
*logit.lrm <- lrm(gotALoan ~ hourlyIncome+ownsHome, data=trainingData)*
*lrm(formula = logit.lrm)$stats[6]*
(output is C 0.8739827 - i.e., just the C-inde...
2007 May 06
3
Neural Nets (nnet) - evaluating success rate of predictions
Hello R-Users,
I have been using (nnet) by Ripley to train a neural net on a test dataset, I have obtained predictions for a validtion dataset using:
PP<-predict(nnetobject,validationdata)
Using PP I can find the -2 log likelihood for the validation datset.
However what I really want to know is how well my nueral net is doing at classifying my binary output variable. I am new to R and I can't figure out how you can assess the success rates of predictions.
Any help and example...