Usually for binary classification problem we find these two parameters and for multi-class problem we find out confusion matrix to check how accurately the samples of different classes are predicted.
Hello Santanu, Here i have given few points what i am using in work this may helpful to you,
1. Give appropriate decision weights (profit matrix)
2. Undersample on the majority class or "good" records.
3. Running a decision tree on the sample.
but you have not specified on which data you are working.
I think referring to the following article will be useful.
M. Sokolova, G. Lapalme, A systematic analysis of performance measures for classification tasks, J. Inform. Process. Manage. 45 (2009)
427–437.
Regards
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