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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define True Positives.
💡 Hint: Think about what happens when the model gets a positive case right.
Question 2
Easy
What does a False Positive indicate?
💡 Hint: Consider the mistakes a model could make in predictions.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does a confusion matrix help to visualize?
- Classification results
- Regression results
- Data pre-processing
💡 Hint: Think about what category of models uses confusion matrices.
Question 2
True or False: True Negatives (TN) indicates correct predictions of negative cases.
- True
- False
💡 Hint: Consider how the terms are defined.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are tasked with improving a classification model for a credit approval system. The confusion matrix shows high false negatives. Discuss strategies to reduce them and enhance the model's recall.
💡 Hint: Consider aspects of model training and evaluation.
Question 2
Given a confusion matrix with TP = 40, FP = 25, FN = 15, and TN = 20, calculate precision, recall, and the F1 Score. Discuss how these metrics could inform model improvement.
💡 Hint: Make sure to follow through the calculations accurately.
Challenge and get performance evaluation