
    Design an algorithm for the bank's fraud detection system that determines the number of possible ways to group n distinct transaction patterns into different behavioral clusters, where each transaction pattern must belong to exactly one cluster and no cluster can be empty. Each unique grouping arrangement represents a different fraud detection strategy, helping analysts identify potential suspicious activities through pattern recognition.
    

    
def bell_number(n):
    """
    Design an algorithm for the bank's fraud detection system that determines the number of possible ways to group n distinct transaction patterns into different behavioral clusters, where each transaction pattern must belong to exactly one cluster and no cluster can be empty. Each unique grouping arrangement represents a different fraud detection strategy, helping analysts identify potential suspicious activities through pattern recognition.
    

    """
def bell_number(n):
    """
    Design an algorithm for the bank's fraud detection system that determines the number of possible ways to group n distinct transaction patterns into different behavioral clusters, where each transaction pattern must belong to exactly one cluster and no cluster can be empty. Each unique grouping arrangement represents a different fraud detection strategy, helping analysts identify potential suspicious activities through pattern recognition.
    

    """
    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]