Imbalanced class metrics
Class imbalance is something that can hamper your model's performance in any machine learning context. This is especially relevant in a machine learning interview if you are asked what to do if you are given a dataset with an imbalanced class, as some data is imbalanced by design such as insurance fraud data.
In this exercise you'll use sklearn to create a logistic regression model and print the confusion matrix along with several evaluation metrics to get a better understanding of how to interpret Machine Learning models from datasets that have a class imbalance.
Recall the class imbalance you saw previously in loan_data. The number of observations with Loan Status of Fully Paid far outweighs those that are Charged Off:
This exercise is part of the course
Practicing Machine Learning Interview Questions in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Import
from sklearn.____ import ____
from sklearn.____ import ____, ____, ____, ____, _____