def normalized_table_calc(classes, table):
    """
    Return normalized confusion matrix.

    :param classes: classes list
    :type classes:list
    :param table: table
    :type table:dict
    :return: normalized table as dict
    """
    map_dict = {k: 0 for k in classes}
    new_table = {k: map_dict.copy() for k in classes}
    for key in classes:
        div = sum(table[key].values())
        if div == 0:
            div = 1
        for item in classes:
            new_table[key][item] = numpy.around(table[key][item] / div, 5)
    return new_table
Return normalized confusion matrix.

    :param classes: classes list
    :type classes:list
    :param table: table
    :type table:dict
    :return: normalized table as dict