code: def hmine_driver(
      item: list,
      itemsets: np.array,
      minsup: int,
      itemsets_shape: int,
      max_len: int,
      verbose: int,
      single_items: np.array,
      frequent_itemsets: dict,
  ) -> dict:
      """
      Driver function for the hmine algorithm.
      Recursively generates frequent itemsets.
      Also works for sparse matrix.
      egg: item = [1] -> [1,2] -> [1,2,3] -> [1,2,4] -> [1,2,5]
      For more info, see
      https://rasbt.github.io/mlxtend/user_guide/frequent_patterns/hmine/
  
      Args:
          item (list): list of items
          itemsets (np.array): matrix of bools or binary
          minsup (int): minimum absolute support
          itemsets_shape (int): number of transactions
          single_items (np.array): array of single items
          max_len (int): maximum length of frequent itemsets
          verbose (int): verbose mode
          frequent_itemsets (dict): dictionary of frequent itemsets
  
      Returns:
          frequent_itemsets(dict): dictionary of frequent itemsets
      """
      # Early stopping if the length of the item is greater than max_len
      if max_len and len(item) >= max_len:
          return frequent_itemsets
      projected_itemsets = create_projected_itemsets(item, itemsets)
      initial_supports = np.array(
          np.sum(projected_itemsets, axis=0)
      ).reshape(-1)
      suffixes = np.nonzero(initial_supports >= minsup)[0]
      suffixes = suffixes[np.nonzero(suffixes > item[-1])[0]]
  
      if verbose:
          print(
              f"{len(suffixes)} itemset(s) from the suffixes on item(s) ({', '.join(single_items[item])})"
          )
      for suffix in suffixes:
          new_item = item.copy()
          new_item.append(suffix)
          supp = initial_supports[suffix] / itemsets_shape
          frequent_itemsets[frozenset(single_items[new_item])] = supp
          # Recursive call to find frequent itemsets
          frequent_itemsets = hmine_driver(
              new_item,
              projected_itemsets,
              minsup,
              itemsets_shape,
              max_len,
              verbose,
              single_items,
              frequent_itemsets,
          )
      return frequent_itemsets
  
imports: import math
  import numpy
  import pandas
  from ..frequent_patterns import fpcommon
label_desc: Use image node_id 3 for calling a global function with example usage: hmine_driver(item, itemsets, minsup, itemsets_shape, max_len, verbose, single_items, frequent_itemsets) and returns: frequent_itemsets, frequent_itemsets