code: def _find_relevance_chunks(log_ttd, log_lift, R, lambda_seq):
      return pd.concat(
          [
              _find_relevance(log_ttd, log_lift, R, seq)
              for seq in lambda_seq
          ]
      )
  
imports: import json
  import logging
  import numpy
  import pandas
  from collections import namedtuple
  from joblib import Parallel, delayed, cpu_count
  from scipy.stats import entropy
  from scipy.spatial.distance import pdist, squareform
  from sklearn.manifold import MDS, TSNE
  from pyLDAvis.utils import NumPyEncoder
label_desc: Use image node_id 15 for calling a global function with example usage: _find_relevance_chunks(log_ttd, log_lift, R, lambda_seq) and returns: pd