我正在尝试使用ROCR包从分析中导出生物识别数据.这是我到目前为止所做的代码:
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.values":
[[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
.......
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这导致几个插槽.我想使用以下结果将结果值导出到Excel修改的文本文件中:
write(pred, "filename")
但是,当我尝试编写该文件时,我收到一条错误消息:
Error in cat(list(...), file, sep, fill, labels, append) :
argument 1 (type 'S4') cannot be handled by 'cat'
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有没有办法解决?
我很感激任何建议.谢谢!
马特彼得森
检查生成的S4对象的类结构str,提取相关变量以构建数据帧并使用write.table/ write.csv导出结果.例如,对于预测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")
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和表现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")
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