Neuronet: X:\work\projects\FuzzyClassificator_dohq\network.xml

FuzzyScale = {Min, Low, Med, High, Max}
    Min = <Hyperbolic(x, {"a": 8, "b": 20, "c": 0}), [0.0, 0.23]>
    Low = <Bell(x, {"a": 0.17, "b": 0.23, "c": 0.34}), [0.17, 0.4]>
    Med = <Bell(x, {"a": 0.34, "b": 0.4, "c": 0.6}), [0.34, 0.66]>
    High = <Bell(x, {"a": 0.6, "b": 0.66, "c": 0.77}), [0.6, 0.83]>
    Max = <Parabolic(x, {"a": 0.77, "b": 0.95}), [0.77, 1.0]>

Classification results for candidates vectors:

    Header: [input1 input2 input3]	[1st_class_output 2nd_class_output]
    -----------------------------------------------------------------------
    Input: ['0.12', '0.32', 'Min']	Output: ['Med', 'Med']
    Input: ['0.32', '0.35', 'Low']	Output: ['High', 'Low']
    Input: ['0.54', '0.57', 'Med']	Output: ['Max', 'Min']
    Input: ['0.65', '0.68', 'High']	Output: ['Max', 'Min']
    Input: ['0.76', '0.79', 'Max']	Output: ['Max', 'Min']
