code: def test_raises_error(dataset):
      mod_quantile = LinearRegression()
      clf_quantile = OutlierClassifier(mod_quantile)
      X = dataset
      y = (dataset.max(axis=1) > 3).astype(int)
      with pytest.raises(ValueError):
          clf_quantile.fit(X, y)
  
file_path: scikit-lego/tests/test_meta/test_outlier_classifier.py
imports: import numpy
  import pytest
  from sklearn.ensemble import IsolationForest
  from sklearn.linear_model import LinearRegression
  from sklearn.neighbors import LocalOutlierFactor
  from sklearn.svm import OneClassSVM
  from sklego.common import flatten
  from sklego.meta import OutlierClassifier
  from sklego.mixture import GMMOutlierDetector
  from tests.conftest import general_checks, select_tests
label_desc: Use image node_id 4 for calling a global function with example usage: test_raises_error(dataset) without return types