Calculate Goodman and Kruskal's lambda A.

    :param classes: confusion matrix classes
    :type classes : list
    :param table: confusion matrix table
    :type table : dict
    :param P: condition positive
    :type P : dict
    :param POP: population
    :type POP : int
    :return: Goodman and Kruskal's lambda A as float

def lambda_A_calc(classes, table, P, POP):
    """
    Calculate Goodman and Kruskal's lambda A.

    :param classes: confusion matrix classes
    :type classes : list
    :param table: confusion matrix table
    :type table : dict
    :param P: condition positive
    :type P : dict
    :param POP: population
    :type POP : int
    :return: Goodman and Kruskal's lambda A as float
    """
    try:
        result = 0
        maxreference = max(list(P.values()))
        length = POP
        for i in classes:
            col = []
            for col_item in table.values():
                col.append(col_item[i])
            result += max(col)
        result = (result - maxreference) / (length - maxreference)
        return result
    except Exception:
        return "None"