code: def test_restricted_characters_in_feature_name(self):
      df = pd.DataFrame(
          {
              "y": np.random.randint(0, 2, size=100),
              "[test1]": np.random.uniform(0, 1, size=100),
              "test2 < 1": np.random.uniform(0, 1, size=100),
          }
      )
  
      y = df.iloc[:, 0]
      X = df.iloc[:, 1:]
  
      metric = Metric({"name": "logloss"})
      params = {
          "objective": "binary:logistic",
          "eval_metric": "logloss",
          "ml_task": BINARY_CLASSIFICATION,
      }
      xgb = XgbAlgorithm(params)
      xgb.fit(X, y)
      xgb.predict(X)
  
imports: import unittest
  import tempfile
  import json
  import numpy
  import pandas
  import os
  from numpy.testing import assert_almost_equal
  from sklearn import datasets
  from supervised.algorithms.xgboost import XgbAlgorithm, additional
  from supervised.utils.metric import Metric
  from supervised.utils.constants import BINARY_CLASSIFICATION
  import tempfile
label_desc: Use image node_id 6 for calling the XgboostAlgorithmTest obj's underlying member method code with example usage: obj.test_restricted_characters_in_feature_name() without return types