code: def create_fixed_training_data(self) -> pd.DataFrame:
      users = [
          6,
          2,
          8,
          6,
          7,
          8,
          2,
          8,
          10,
          3,
          11,
          6,
          7,
          3,
          2,
          10,
          11,
          1,
          8,
          4,
          9,
          3,
          5,
          6,
          7,
      ]
  
      resources = [
          2,
          8,
          2,
          8,
          2,
          6,
          4,
          1,
          5,
          5,
          6,
          1,
          6,
          7,
          6,
          3,
          3,
          4,
          4,
          8,
          2,
          1,
          7,
          7,
          5,
      ]
  
      likelihoods = [
          1.0,
          1.0,
          1.0,
          1.0,
          1.0,
          1.0,
          1.0,
          1.0,
          1.0,
          1.0,
          1.0,
          1.0,
          1.0,
          1.0,
          46.77678298950195,
          35.94552993774414,
          36.470367431640625,
          33.59884262084961,
          10.0,
          43.84599304199219,
          14.908903121948242,
          10.0,
          19.817806243896484,
          21.398120880126953,
          14.908903121948242,
      ]
  
      return self.to_pdf(users, resources, likelihoods)
  
file_path: SynapseML/core/src/main/python/synapse/ml/cyber/dataset.py
imports: from typing import List, Set, Optional, Tuple
  import pandas
  import random
  from synapse.ml.cyber.anomaly.collaborative_filtering import AccessAnomalyConfig
label_desc: Use image node_id 8 for calling the DataFactory obj's underlying member method code with example usage: obj.create_fixed_training_data() and returns: self