How to export data from ROCR package

I am trying to export biometric data from an analysis using the ROCR package. Here is the code that I've done so far:

pred = performance(Matching.Score,Distribution)
perf = prediction(pred,"fnr", "fpr")

An object of class “performance”

Slot "x.name":

[1] "False positive rate"

Slot "y.name":

[1] "False negative rate"

Slot "alpha.name":

[1] "Cutoff"

Slot "x.values":

[[1]]

[1] 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
[15] 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000
  ......

Slot "y.value开发者_运维技巧s":

[[1]]

[1] 1.00000 0.99999 0.99998 0.99997 0.99996 0.99995
[15] 0.99986 0.99985 0.99984 0.99983 0.99982 0.99981
    ......

Slot "alpha.values":

[[1]]

[1]  Inf      1.0427800 1.0221150 1.0056240 1.0032630 0.9999599
[12] 0.9644779 0.9633058 0.9628996 0.9626501 0.9607665 0.9605930
    .......

This results in several Slots. I would like to export the resulting values into a text file for Excel modification using:

write(pred, "filename")

However, when I try to write the file, I get an error stating:

Error in cat(list(...), file, sep, fill, labels, append) : 
  argument 1 (type 'S4') cannot be handled by 'cat'

Is there any way around this?

I'd appreciate any advice. Thank you!

Matt Peterson

Check the class structure of the resulting S4 objects with str, extract the relevant variables to build a dataframe and use write.table/write.csv to export the results. For instance, for the prediction pred:

R> library("ROCR")
R> data(ROCR.simple)
R> pred <- prediction(ROCR.simple$predictions, ROCR.simple$labels)
R> perf <- performance(pred, "fnr", "fpr")
R> str(pred)
Formal class 'prediction' [package "ROCR"] with 11 slots
  ..@ predictions:List of 1
  .. ..$ : num [1:200] 0.613 0.364 0.432 0.14 0.385 ...
  ..@ labels     :List of 1
  .. ..$ : Ord.factor w/ 2 levels "0"<"1": 2 2 1 1 1 2 2 2 2 1 ...
  ..@ cutoffs    :List of 1
  .. ..$ : num [1:201] Inf 0.991 0.985 0.985 0.983 ...
  ..@ fp         :List of 1
  .. ..$ : num [1:201] 0 0 0 0 1 1 2 3 3 3 ...
  ..@ tp         :List of 1
  .. ..$ : num [1:201] 0 1 2 3 3 4 4 4 5 6 ...
  ..@ tn         :List of 1
  .. ..$ : num [1:201] 107 107 107 107 106 106 105 104 104 104 ...
  ..@ fn         :List of 1
  .. ..$ : num [1:201] 93 92 91 90 90 89 89 89 88 87 ...
  ..@ n.pos      :List of 1
  .. ..$ : int 93
  ..@ n.neg      :List of 1
  .. ..$ : int 107
  ..@ n.pos.pred :List of 1
  .. ..$ : num [1:201] 0 1 2 3 4 5 6 7 8 9 ...
  ..@ n.neg.pred :List of 1
  .. ..$ : num [1:201] 200 199 198 197 196 195 194 193 192 191 ...

R> write.csv(data.frame(fp=pred@fp, fn=pred@fn), file="result_pred.csv")

and for performance perf:

R> str(perf)
Formal class 'performance' [package "ROCR"] with 6 slots
  ..@ x.name      : chr "False positive rate"
  ..@ y.name      : chr "False negative rate"
  ..@ alpha.name  : chr "Cutoff"
  ..@ x.values    :List of 1
  .. ..$ : num [1:201] 0 0 0 0 0.00935 ...
  ..@ y.values    :List of 1
  .. ..$ : num [1:201] 1 0.989 0.978 0.968 0.968 ...
  ..@ alpha.values:List of 1
  .. ..$ : num [1:201] Inf 0.991 0.985 0.985 0.983 ...

R> write.csv(data.frame(fpr=perf@x.values,
                        fnr=perf@y.values, 
                        alpha.values=perf@alpha.values), 
             file="result_perf.csv")