Number of Inputs: 24

Nature of Inputs:
    Numbers that result either from adding
    a pseudo-random number to the previous number,
    (Low-Pass Filter),
    Or from subtracting the previous number
    from the current pseudo-random number,
    (High-Pass Filter).
    Based on evenly-distributed pseudo-random
    numbers from -1.0 to +1.0

Expected Output:
    0 if a Low-Pass Filter was used,
    1 if a High-Pass Filter was used.

Number of Sets: (100 + 100) * 2


"GA_BestTrain.cpp"
Best of Training Accuracy: 100%
Corresponding Validation Accuracy: 79%

"GA_BestValid.cpp"
Best of Validation Accuracy: 80%

Using Data from Human Program "HLPass-gp.cpp"

Training Data: "Out1.txt"
Validation Data: "Out2.txt"