Hi everyone.
    Probably this is statistical question rather than an R, but it involves
packages from R I am asking here since I am unable to find an answer. In the
parametric modeling packages like glmnet, lasso etc......., we are able to
obtain the coeffcients that have entered the model.

for eg in glmnet if we are working on a dataset containing 15 variables
the coeffecient parameters output is like this, from the below result we
know that 5 variables or features have entered the model and are chosen and
the rest 10 variables have not entered, can we plot an ROC curve detremine
sensitivity, specificity and confusion matrix using just this below
information. any input would be great.

0.000
0.01213
-0.1213
0.0000
0.0000
0.0000
0.0000
-0.00034
0.0000
0.0000
0.0000
0.0000
0.0023
0.0988
0.0000

thanks
vss

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