class_docstr: Test ClassPredictionError visualizer
class_docstr_tok: ["Test","ClassPredictionError","visualizer"]
docstr: Test that ClassPredictionError score() returns a score between 0 and 1
docstr_tok: ["Test","that","ClassPredictionError","score","(",")","returns","a","score","between","0","and","1"]
code: def test_score_returns_score(self):
      """
      Test that ClassPredictionError score() returns a score between 0 and 1
      """
      X, y = load_occupancy(return_dataset=True).to_numpy()
  
      # Create and fit the visualizer
      visualizer = ClassPredictionError(LinearSVC(random_state=42))
      visualizer.fit(X, y)
  
      # Score the visualizer
      s = visualizer.score(X, y)
      assert 0 <= s <= 1
  
imports: import pytest
  import matplotlib.pyplot
  from yellowbrick.exceptions import ModelError
  from yellowbrick.datasets import load_occupancy
  from yellowbrick.classifier.class_prediction_error import *
  from sklearn.svm import LinearSVC, SVC
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.datasets import make_multilabel_classification
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import MinMaxScaler
  from unittest.mock import patch
  from tests.base import VisualTestCase
label_desc: Use image node_id 10 for calling the TestClassPredictionError obj's underlying member method code with example usage: obj.test_score_returns_score() without return types