Let us visualize the confusion matrices for the predictions made on the test set and over-sampled train set.
Note:
plot_confusion_matrix(estimator, X, y) plots Confusion Matrix. Here estimator is the fitted classifier, X is the input values and y is the target values.
Import plot_confusion_matrix from sklearn.metrics
from << your code comes here >> import << your code comes here >>
Write the class names.
class_names = ['Not Fraud', 'Fraud']
Call the plot_confusion_matrix function and pass k, X_test, y_test as arguments.
<< your code comes here >>(k, X_test, y_test, values_format = '.5g', display_labels=class_names)
plt.title("Test data Confusion Matrix")
plt.show()
Call the plot_confusion_matrix function and pass k, X_train_res, y_train_res as arguments.
<< your code comes here >>(k, X_train_res, y_train_res, values_format = '.5g', display_labels=class_names)
plt.title("Oversampled Train data Confusion Matrix")
plt.show()
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