[R] no true negative data, need roc curve

[Jessica Streicher]

Just to say, i still consider it wrong (what is called the fpr there simply isn't the fpr, and the graph will not be what is commonly known as an ROC curve), at least the definition list puts down slightly different names for it.
What else exactly do you need then though? you now know how to plot points and lines, whats there more to explain? 

You can use the commands ?plot ? points ?lines and so on to find help on it.

On 17.08.2012, at 13:18, Jessica Streicher wrote:

> Above mentioned formula is wrong - maybe a typo
> http://en.wikipedia.org/wiki/Receiver_operating_characteristic
> 
> The false positive rate is the rate of false positives, meaning how many of the total negatives (all in reality negatives(N), that is, all negatives falsely classified as positives(fp) and all negatives correctly classified as negatives(tn)) have been falsely classified as positive.
> 
> Also the authors obviously had (N+P=number of features), and therefore at least could have computed this properly. For example:
> 
> N+P=100
> P=TP+FN
> N=FP+TN
> -> do the math with what you got
> 
> On 17.08.2012, at 11:13, vjyns wrote:
> 
>> Hi,
>> 
>>    thanks for the quick response, but as i said in my case due to two
>> different threshold the detected features will differ. Moreover, there is
>> some standard /refined/ formula in calculating the tpr and fpr. herewith i
>> had attached the refined formula from a standard international journal 
>> http://r.789695.n4.nabble.com/file/n4640577/tpr_and_fpr.jpg 
>> 
>> when i used the above mentioned formula (fpr=fp/fp+tp) then i can able to
>> see my point are distributed on the extreme left corner. Like this it is
>> possible to put all the 6 images.  Will you please suggest me now how to
>> obtain the plot for different images of two threshold. 
>> 
>> 
>> 
>> --
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>> 
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