Class BinaryErrorStats

Parameters:

• err_array (array of 5 doubles) - err_array[0] : FAR err_array[1] : FRR err_array[2] : total weight of class 0 err_array[3] : total weight of class 1

Get the objective function value.

There are four different criteria to consider:

• Minimize the error rate: lambda * p(pos)*FRR + p(neg)*FAR
• Minimize the error rate without prior: lambda * FRR + FAR
• Minimize FAR with constraint FRR <= maxFRR
• Minimize FRR with constraint FAR <= maxFAR

Parameters:

• criterion (integer from 0 to 3) - 0: minimize the error rate with prior probabilities 1: minimize the error rate without prior probabilities 2: minimize FAR while constraining FRR 3: minimize FRR while constraining FAR
• param1 (double) -

  a parameter representing

  lambda if criterion < 2 maxFRR if criterion == 2 maxFAR if criterion == 3

Returns:

objective function value based on the given criterion An InfeasibleSolution exception is raised if necessary