Function find_prefix_path

machine_learning/frequent_pattern_growth.py:243–276

Find the conditional pattern base for a given base pattern. Args: base_pat: The base pattern for which to find the conditional pattern base. tree_node: The node in the FP-Tree. Example: >>> data_set = [ ... ['A', 'B', 'C'], ... ['A', 'C'], ...

(base_pat: frozenset, tree_node: TreeNode | None)

def find_prefix_path(base_pat: frozenset, tree_node: TreeNode | None) -> dict:  # noqa: ARG001
    """
    Find the conditional pattern base for a given base pattern.

    Args:
        base_pat: The base pattern for which to find the conditional pattern base.
        tree_node: The node in the FP-Tree.

    Example:
    >>> data_set = [
    ...    ['A', 'B', 'C'],
    ...    ['A', 'C'],
    ...    ['A', 'B', 'E'],
    ...    ['A', 'B', 'C', 'E'],
    ...    ['B', 'E']
    ... ]
    >>> min_sup = 2
    >>> fp_tree, header_table = create_tree(data_set, min_sup)
    >>> fp_tree
    TreeNode('Null Set', 1, None)
    >>> len(header_table)
    4
    >>> base_pattern = frozenset(['A'])
    >>> sorted(find_prefix_path(base_pattern, fp_tree.children['A']))
    []
    """
    cond_pats: dict = {}
    while tree_node is not None:
        prefix_path: list = []
        ascend_tree(tree_node, prefix_path)
        if len(prefix_path) > 1:
            cond_pats[frozenset(prefix_path[1:])] = tree_node.count
        tree_node = tree_node.node_link
    return cond_pats


def mine_tree(