code: def test_632plus():
      tree = DecisionTreeClassifier(random_state=123)
      scores = bootstrap_point632_score(
          tree, X, y, random_seed=123, method=".632+"
      )
      acc = np.mean(scores)
      assert len(scores == 200)
      assert np.round(acc, 5) == 0.95855, np.round(acc, 5)
  
      tree2 = DecisionTreeClassifier(random_state=123, max_depth=1)
      scores = bootstrap_point632_score(
          tree2, X, y, random_seed=123, method=".632+"
      )
      acc = np.mean(scores)
      assert len(scores == 200)
      assert np.round(acc, 5) == 0.64078, np.round(acc, 5)
  
imports: import os
  import numpy
  import pandas
  import pytest
  from sklearn.base import BaseEstimator
  from sklearn.linear_model import LogisticRegression
  from sklearn.tree import DecisionTreeClassifier
  from mlxtend.data import iris_data
  from mlxtend.evaluate import bootstrap_point632_score
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 5 for calling a global function with example usage: test_632plus() without return types