code: def _split_instances(
      pos: np.ndarray, neg: np.ndarray, ratio, random_state
  ):
      pos_train, pos_prune = train_test_split(
          pos, random_state=random_state, train_size=ratio
      )
      neg_train, neg_prune = train_test_split(
          neg, random_state=random_state, train_size=ratio
      )
  
      return pos_train, pos_prune, neg_train, neg_prune
  
file_path: AIX360/aix360/algorithms/rule_induction/ripper/base.py
imports: import sys
  import numpy
  from pandas import DataFrame
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import LabelEncoder
  from aix360.algorithms.rule_induction.ripper.binding import EQ, LE, GE
label_desc: Use image node_id 4 for calling a global function with example usage: _split_instances(pos, neg, ratio, random_state) and returns: pos_train,  pos_prune,  neg_train,  neg_prune