code: def make_dataset(
      n_samples=256,
      n_features=5,
      n_classes=2,
      test_size=0.5,
      shuffle=True,
  ):
      x, y = make_classification(
          n_samples=n_samples,
          n_features=n_features,
          n_classes=n_classes,
          random_state=777,
      )
      return train_test_split(
          x, y, random_state=777, test_size=test_size, shuffle=shuffle
      )
  
file_path: scikit-learn-intelex/daal4py/sklearn/test/test_common.py
imports: import numpy
  import pandas
  import pytest
  from sklearn.datasets import make_classification
  from sklearn.model_selection import train_test_split
  from daal4py.sklearn.ensemble import RandomForestClassifier
  from daal4py.sklearn.ensemble import RandomForestRegressor
  from daal4py.sklearn.neighbors import KNeighborsClassifier
label_desc: Use image node_id 2 for calling a global function with example usage: make_dataset(n_samples, n_features, n_classes, test_size, shuffle) and returns: train_test_split