
    Given n distinct student risk indicators (such as poor attendance, failing grades, and behavioral issues), determine the number of different ways these indicators can be grouped into risk categories to identify potential dropout patterns. Each risk indicator must be assigned to exactly one category, and the function should calculate all possible valid categorization schemes that could help in early intervention strategies.
    

    
def bell_number(n):
    """
    Given n distinct student risk indicators (such as poor attendance, failing grades, and behavioral issues), determine the number of different ways these indicators can be grouped into risk categories to identify potential dropout patterns. Each risk indicator must be assigned to exactly one category, and the function should calculate all possible valid categorization schemes that could help in early intervention strategies.
    

    """
def bell_number(n):
    """
    Given n distinct student risk indicators (such as poor attendance, failing grades, and behavioral issues), determine the number of different ways these indicators can be grouped into risk categories to identify potential dropout patterns. Each risk indicator must be assigned to exactly one category, and the function should calculate all possible valid categorization schemes that could help in early intervention strategies.
    

    """
    bell = [[0 for i in range(n + 1)] for j in range(n + 1)]
    bell[0][0] = 1
    for i in range(1, n + 1):
        bell[i][0] = bell[i - 1][i - 1]
        for j in range(1, i + 1):
            bell[i][j] = bell[i - 1][j - 1] + bell[i][j - 1]
    return bell[n][0]