code: def roc_multi_classification_raw_data(target_analysis_multiclass):
      X_train, X_test, y_train, y_test = target_analysis_multiclass
      classifier = LogisticRegression()
      y_score = classifier.fit(X_train, y_train).predict_proba(X_test)
  
      return y_test, y_score
  
imports: from copy import copy
  import sys
  import os
  from pathlib import Path
  import numpy
  from sklearn.linear_model import LogisticRegression
  import pytest
  from matplotlib.testing.conftest import mpl_test_settings, mpl_image_comparison_parameters
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import GridSearchCV
  from sklearn import datasets
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 12 for calling a global function with example usage: roc_multi_classification_raw_data(target_analysis_multiclass) and returns: y_test,  y_score