code: def jaccard_dissim_label(a, b, **__):
      """Jaccard dissimilarity function for label encoded variables"""
      if (
          np.isnan(a.astype("float64")).any()
          or np.isnan(b.astype("float64")).any()
      ):
          raise ValueError(
              "Missing values detected in Numeric columns."
          )
      intersect_len = np.empty(len(a), dtype=int)
      union_len = np.empty(len(a), dtype=int)
      ii = 0
      for row in a:
          intersect_len[ii] = len(np.intersect1d(row, b))
          union_len[ii] = (
              len(np.unique(row))
              + len(np.unique(b))
              - intersect_len[ii]
          )
          ii += 1
      if (union_len == 0).any():
          raise ValueError(
              "Insufficient Number of data since union is 0"
          )
      return 1 - intersect_len / union_len
  
imports: import numpy
label_desc: Use image node_id 3 for calling a global function with example usage: jaccard_dissim_label(a, b) and returns: unknown