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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def CEN_misclassification_calc( table, TOP, P, i, j, subject_class, modified=False):
 """ Calculate misclassification probability of classifying. :param table: input matrix :type table : dict :param TOP: test outcome positive :type TOP : int :param P: condition positive :type P : int :param i: table row index (class name) :type i : any valid type :param j: table col index (class name) :type j : any valid type :param subject_class: subject to class (class name) :type subject_class: any valid type :param modified : modified mode flag :type modified : bool :return: misclassification probability of classifying as float """

    try:
        result = TOP + P
        if modified:
            result -= table[subject_class][subject_class]
        result = table[i][j] / result
        return result
    except Exception:
        return "None"