code: def epsilon():
      """
      Download "epsilon" [1] data set.
  
      Will return two pandas.DataFrame-s, first with train part (epsilon_normalized) and second with
      test part (epsilon_normalized.t) of the dataset. Object class will be located in the first
      column of dataset.
  
      NOTE: This is a preprocessed version of the dataset. It was converted from libsvm format into
      tsv (CatBoost doesn't support libsvm format out of the box).
  
      [1]: https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/binary.html#epsilon
      """
      urls = (
          "https://proxy.sandbox.yandex-team.ru/785711439",
          "https://storage.mds.yandex.net/get-devtools-opensource/250854/epsilon.tar.gz",
      )
      md5 = "5bbfac403ac673da7d7ee84bd532e973"
      dataset_name, train_file, test_file = (
          "epsilon",
          "train.tsv",
          "test.tsv",
      )
      train_path, test_path = _download_dataset(
          urls, md5, dataset_name, train_file, test_file, cache=True
      )
      return (
          _load_numeric_only_dataset(
              train_path, 400000, 2001, sep="\t"
          ),
          _load_numeric_only_dataset(test_path, 100000, 2001, sep="\t"),
      )
  
imports: import hashlib
  import logging
  import numpy
  import os
  import pandas
  import tarfile
  import tempfile
  import six
  import shutil
  from .core import PATH_TYPES, fspath
label_desc: Use image node_id 16 for calling a global function with example usage: epsilon() and returns: _load_numeric_only_dataset,  _load_numeric_only_dataset