Displaying 8 results from an estimated 8 matches for "auc1".
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acc1
2009 May 12
1
ROCR: auc and logarithm plot
Hi,
I am quite new to R and I have two questions regarding ROCR.
1. I have tried to understand how to extract area-under-curve value by looking at the ROCR document and googling. Still I am not sure if I am doing the right thing. Here is my code, is "auc1" the auc value?
"
pred1 <- prediction(resp1,label1)
perf1 <- performance(pred1,"tpr","fpr")
plot( perf1, type="l",col=1 )
auc1 <- performance(pred1,"auc")
auc1 <- auc1@y.values[[2]]
"
2. I have to compare two models that have ver...
2010 Oct 22
2
Random Forest AUC
...),]
iris$Species <- factor(iris$Species)
fit <- glm(Species~.,iris,family=binomial)
train.predict <- predict(fit,newdata = iris,type="response")
library(ROCR)
plot(performance(prediction(train.predict,iris$Species),"tpr","fpr"),col =
"red")
auc1 <-
performance(prediction(train.predict,iris$Species),"auc")@y.values[[1]]
legend("bottomright",legend=c(paste("Logistic Regression
(AUC=",formatC(auc1,digits=4,format="f"),")",sep="")),
col=c("red"), lty=1)
library(rand...
2008 Jun 12
1
About Mcneil Hanley test for a portion of AUC!
...the function
cROC. I can only find the value of "r" for the whole AUC's .
> seROC<-function(AUC,na,nn){
> a<-AUC
> q1<-a/(2-a)
> q2<-(2*a^2)/(1+a)
> se<-sqrt((a*(1-a)+(na-1)*(q1-a^2)+(nn-1)*(q2-a^2))/(nn*na))
> se
> }
>
> cROC<-function(AUC1,na1,nn1,AUC2,na2,nn2,r){
> se1<-seROC(AUC1,na1,nn1)
> se2<-seROC(AUC2,na2,nn2)
>
> sed<-sqrt(se1^2+se2^2-2*r*se1*se2)
> zad<-(AUC1-AUC2)/sed
> p<-dnorm(zad)
> a<-list(zad,p)
> a
Could somebody kindly suggest me how to calculate the value of "r" o...
2006 Mar 15
1
How to compare areas under ROC curves calculated with ROCR package
...e the AUC.
I used the following program I found on R-help archives :
From: Bernardo Rangel Tura
Date: Thu 16 Dec 2004 - 07:30:37 EST
seROC<-function(AUC,na,nn){
a<-AUC
q1<-a/(2-a)
q2<-(2*a^2)/(1+a)
se<-sqrt((a*(1-a)+(na-1)*(q1-a^2)+(nn-1)*(q2-a^2))/(nn*na))
se
}
cROC<-function(AUC1,na1,nn1,AUC2,na2,nn2,r){
se1<-seROC(AUC1,na1,nn1)
se2<-seROC(AUC2,na2,nn2)
sed<-sqrt(se1^2+se2^2-2*r*se1*se2)
zad<-(AUC1-AUC2)/sed
p<-dnorm(zad)
a<-list(zad,p)
a
}
The author of this script says: "The first function (seROC) calculate the standard error of ROC curve, the
se...
2006 Mar 20
1
How to compare areas under ROC curves calculated with ROC R package
...e the AUC.
I used the following program I found on R-help archives :
From: Bernardo Rangel Tura
Date: Thu 16 Dec 2004 - 07:30:37 EST
seROC<-function(AUC,na,nn){
a<-AUC
q1<-a/(2-a)
q2<-(2*a^2)/(1+a)
se<-sqrt((a*(1-a)+(na-1)*(q1-a^2)+(nn-1)*(q2-a^2))/(nn*na))
se
}
cROC<-function(AUC1,na1,nn1,AUC2,na2,nn2,r){
se1<-seROC(AUC1,na1,nn1)
se2<-seROC(AUC2,na2,nn2)
sed<-sqrt(se1^2+se2^2-2*r*se1*se2)
zad<-(AUC1-AUC2)/sed
p<-dnorm(zad)
a<-list(zad,p)
a
}
The author of this script says: "The first function (seROC) calculate the
standard error of ROC curve, the
se...
2009 Oct 28
1
need help explain the routine input parameters for seROC and cROC found in the R archive
...in advance.
> From: Bernardo Rangel Tura
> Date: Thu 16 Dec 2004 - 07:30:37 EST
>
> seROC<-function(AUC,na,nn){
> a<-AUC
> q1<-a/(2-a)
> q2<-(2*a^2)/(1+a)
> se<-sqrt((a*(1-a)+(na-1)*(q1-a^2)+(nn-1)*(q2-a^2))/(nn*na))
> se
> }
>
> cROC<-function(AUC1,na1,nn1,AUC2,na2,nn2,r){
> se1<-seROC(AUC1,na1,nn1)
> se2<-seROC(AUC2,na2,nn2)
>
> sed<-sqrt(se1^2+se2^2-2*r*se1*se2)
> zad<-(AUC1-AUC2)/sed
> p<-dnorm(zad)
> a<-list(zad,p)
> a
> }
>
--
Waverley @ Palo Alto
2004 Dec 15
3
(no subject)
Dear R-helper,
I would like to compare the AUC of two logistic regression models (same
population). Is it possible with R ?
Thank you
Roman Rouzier
[[alternative HTML version deleted]]
2011 Dec 22
0
randomforest and AUC using 10 fold CV - Plotting results
...(factor(Species) ~ ., data=iris, ntree=50)
train.predict <- predict(fit,iris,type="prob")[,2]
plot(performance(prediction(train.predict,factor(iris$Species)),"tpr","fpr"),col
= "red")
#As expected AUC is 1 because we are using the same dataset to validate
auc1 <-
performance(prediction(train.predict,factor(iris$Species)),"auc")@y.values[[1]]
legend("bottomright",legend=c(paste("Random Forests
(AUC=",formatC(auc1,digits=4,format="f"),")",sep="")),
col=c("red"), lty...