from yellowbrick.classifier.rocauc import roc_auc
from yellowbrick.datasets import load_credit
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split

#Load the classification dataset
X, y = load_credit()

#Create the train and test data
X_train, X_test, y_train, y_test = train_test_split(X,y)

# Instantiate the visualizer with the classification model
model = LogisticRegression()
roc_auc(model, X_train, y_train, X_test=X_test, y_test=y_test, classes=['not_defaulted', 'defaulted'])