The help page for extractPredictions suggests and testing confirms
that the function expects a _list_ of models. The predict function
is suggested as the method to get predictions from a single model.
Giving the argument as a list does work with a single model, however:
> predict(glmmat)
[1] 0.23544700 -0.03144066 0.24465107 0.59015641 0.22073566
0.20842277 0.98223087 0.72512869
[9] 0.79939904 0.48652752 0.53874162
> extractPrediction(list(glmmat))
obs pred model dataType
1 0 0.23544700 glmnet Training
2 0 -0.03144066 glmnet Training
3 0 0.24465107 glmnet Training
4 0 0.59015641 glmnet Training
5 0 0.22073566 glmnet Training
6 0 0.20842277 glmnet Training
7 1 0.98223087 glmnet Training
8 1 0.72512869 glmnet Training
9 1 0.79939904 glmnet Training
10 1 0.48652752 glmnet Training
11 1 0.53874162 glmnet Training
Invoking it the manner you did would create redundant information
since the input was the same as the training set:
> extractPrediction(list(glmmat),testX=x,testY = y)
obs pred model dataType
1 0 0.23544700 glmnet Training
2 0 -0.03144066 glmnet Training
3 0 0.24465107 glmnet Training
4 0 0.59015641 glmnet Training
5 0 0.22073566 glmnet Training
6 0 0.20842277 glmnet Training
7 1 0.98223087 glmnet Training
8 1 0.72512869 glmnet Training
9 1 0.79939904 glmnet Training
10 1 0.48652752 glmnet Training
11 1 0.53874162 glmnet Training
12 0 0.23544700 glmnet Test
13 0 -0.03144066 glmnet Test
14 0 0.24465107 glmnet Test
15 0 0.59015641 glmnet Test
16 0 0.22073566 glmnet Test
17 0 0.20842277 glmnet Test
18 1 0.98223087 glmnet Test
19 1 0.72512869 glmnet Test
20 1 0.79939904 glmnet Test
21 1 0.48652752 glmnet Test
22 1 0.53874162 glmnet Test
--
David
On Jun 8, 2009, at 12:53 PM, milton ruser wrote:
Dear Sunny Vic,
I am forwarding it to the list, to help the helpers :-)
bests..
milton
On Mon, Jun 8, 2009 at 12:41 PM, sunny vic <vss.0...@gmail.com> wrote:
Hi Milton,
here you go
X1=rnorm(11, 50, 10)
X2=rnorm(11, 20, 10)
X3=rnorm(11, 50, 60)
X4=rnorm(11, 10, 2)
X5=rnorm(11, 5, 22)
x<-cbind(X1,X2,X3,X4,X5);
y <- c(0, 0, 0,0,0,0,1,1,1,1,1) ;
tc=trainControl(method="cv", number=10 );
glmmat<-train(x,y,method="glmnet", trControl=tc);
extractPrediction(list(glmmat,testX=x,testY = y));
Error in models[[i]]$finalModel :
$ operator is invalid for atomic vectors
__________________________________________________
to give you more why I included list in the extractPrediction,
without that
it looks for a list of models , so I found that in the help and
used list
which eliminated that error and is now giving something new.
ERROR without List in extractPrediction
extractPrediction(glmmat,testX=x,testY = y);
Error in models[[1]]$trainingData :
$ operator is invalid for atomic vectors
_____________________________________________
I am actually trying to get the confusion matrix so I can calculate
the
accuracy, sensitivity and specificity of the model
cheers
vss
On Mon, Jun 8, 2009 at 10:42 AM, milton ruser
<milton.ru...@gmail.com>wrote:
Hi Sonny Vic,
how about you send a reproducible code?
cheers
milton
On Mon, Jun 8, 2009 at 11:25 AM, sunny vic <vss.0...@gmail.com>
wrote:
Hi all
I am using the caret package and having difficulty in obtaining the
results
using regression, I used the glmnet to model and trying to get the
coefficients and the model parameters I am trying to use the
extractPrediction to obtain a confusion matrix and it seems to be
giving
me
errors.
x<-read.csv("x.csv", header=TRUE);
y<-read.csv("y.csv", header=TRUE);
tc=trainControl(method="cv", number=10 );
glmmat<-train(x,y,method="glmnet", trControl=tc);
extractPrediction(list(glmmat,testX=x,testY = y));
any help would be great
thanks
vss
--
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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