Better would be 100 repeats of 10-fold cross-validation, or
bootstrapping, as implemented in the rms package.
Frank
On 05/26/2010 08:21 AM, azam jaafari wrote:
Hi
Thank you for your reply.
I'm new in R. So I'm slow
If I want to do leave-one-out cross validation with these data(100), how I tell
R that omit one by one data? Is validationsize=100?
Thanks alot
Azam
--- On Wed, 5/26/10, Joris Meys<jorism...@gmail.com> wrote:
From: Joris Meys<jorism...@gmail.com>
Subject: Re: [R] validation logistic regression
To: "azam jaafari"<azamjaaf...@yahoo.com>
Cc: r-help@r-project.org
Date: Wednesday, May 26, 2010, 5:00 AM
Hi,
first of all, you shouldn't backtransform your prediction, use the option
type=response instead :
salichpred<-predict(salic.lr, newdata=profilevalidation,type="response")
limit<- 0.5
salichpredcat<- ifelse(salichpred<limit,0,1) # prediction of categories.
Read in on sensitivity, specificity and ROC-curves. With changing the limit,
you can calculate sensitivity and specificity, and you can construct a ROC
curve that will tell you how well your predictions are. It all depends on how
much error you allow on the predictions.
Cheers
Joris
On Wed, May 26, 2010 at 10:04 AM, azam jaafari<azamjaaf...@yahoo.com> wrote:
Hi
I did validation for prediction by logistic regression according to following:
validationsize<- 23
set.seed(1)
random<-runif(123)
order(random)
nrprofilesinsample<-sort(order(random)[1:100])
profilesample<- data[nrprofilesinsample,]
profilevalidation<- data[-nrprofilesinsample,]
salich<-profilesample$SALIC.H.1
salic.lr<-glm(salich~wetnessindex, profilesample, family=binomial('logit'))
summary(salic.lr)
salichpred<-predict(salic.lr, newdata=profilevalidation)
expsalichpred<-exp(salichpred)
salichprediction<-(expsalichpred/(1+expsalichpred))
So,
table(salichprediction, profilevalidation$SALIC.H.1)
in result:
salichprediction 0 1
0.0408806327422231 1 0
0.094509645033899 1 0
0.118665480273383 1 0
0.129685441514168 1 0
0.13545295569511 1 0
0.137580612201769 1 0
0.197265822234215 1 0
0.199278585548248 0 1
0.202436276322278 1 0
0.211278767985746 1 0
0.261036846823867 1 0
0.283792703256058 1 0
0.362229486187581 0 1
0.362795636267779 1 0
0.409067386115694 1 0
0.410860613509484 0 1
0.423960962956254 1 0
0.428164288793652 1 0
0.448509687866763 0 1
0.538401659478058 0 1
0.557282539294224 1 0
0.603881788227797 0 1
0.63633478460736 0 1
So, I have salichprediction between 0 to 1 and binary variable(observed values)
0 or 1. I want to compare these data together and I want to know is ok this
model(logistic regression) for prediction or no?
please help me?
Thanks alot
Azam
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--
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______________________________________________
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