Hi,
I am performing analysis of SVM, Decision Trees, Neural Network and Random Forest in EM and getting True Positve Rate, False Positive Rate etc for each of these 4 algos, I have a binary target variable called category with 1 for allergic and 0 for non allergic.
I know roughly that if i get TPR then it means allergic and FPR means false alarm of non allergic treated as allergic. (Dont know whether I am right or wrong)
could anyone tell me how can i declare allergic =1 as my positive class so that I can say for sure that this definitly means allergic.
And where should I declare this?
Regards
In the Enterprise Miner Reference Help, Model Comparison node chapter, the section Comparing Models with Binary Targets gives a nice chart showing what exactly these rates represent (shown below, but not formatted well). It mentions that typically the value 1 is treated as the target event, and 0 as the non-event. This is controlled by the Order that is set for the target variable in the Input Data node or a Metadata node. For a binary target, the order by default is Descending, which means the first value when sorting the target levels in descending order is used as the event (hence 1 if values are 0 and 1). Hope that helps...
|
Predicted Non-Event |
Predicted Event |
Total Actual Probability |
---|---|---|---|
Non-Event |
A (true negative) |
B (false positive) |
(A + B) / (A + B + C + D ) |
Event |
C (false negative) |
D (true positive) |
(C + D) / (A + B + C + D ) |
Total Predicted |
A + C |
B + D |
A + B + C + D |
The following classification measures are derived from the relationships in the table:
In the Enterprise Miner Reference Help, Model Comparison node chapter, the section Comparing Models with Binary Targets gives a nice chart showing what exactly these rates represent (shown below, but not formatted well). It mentions that typically the value 1 is treated as the target event, and 0 as the non-event. This is controlled by the Order that is set for the target variable in the Input Data node or a Metadata node. For a binary target, the order by default is Descending, which means the first value when sorting the target levels in descending order is used as the event (hence 1 if values are 0 and 1). Hope that helps...
|
Predicted Non-Event |
Predicted Event |
Total Actual Probability |
---|---|---|---|
Non-Event |
A (true negative) |
B (false positive) |
(A + B) / (A + B + C + D ) |
Event |
C (false negative) |
D (true positive) |
(C + D) / (A + B + C + D ) |
Total Predicted |
A + C |
B + D |
A + B + C + D |
The following classification measures are derived from the relationships in the table:
Hi,
Thanks for your reply which is very helpful.
Cleared my concept further.
Regards
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