Practice Step 6: Evaluate the Model - 9.7 | Chapter 9: End-to-End Machine Learning Project – Predicting Student Exam Performance | Machine Learning Basics
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Step 6: Evaluate the Model

9.7 - Step 6: Evaluate the Model

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

Define accuracy in the context of model evaluation.

💡 Hint: Think about the total number of cases and correct predictions.

Question 2 Easy

What does precision indicate?

💡 Hint: Focus on true positives versus predicted positives.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is a confusion matrix used for?

To count incorrect predictions
To assess model performance
To display training data

💡 Hint: Think about where this matrix is applied.

Question 2

True or False: High accuracy always indicates a good model.

True
False

💡 Hint: Consider cases where one outcome is much more frequent than the other.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a confusion matrix with TP = 30, TN = 50, FP = 10, FN = 5, calculate the accuracy, precision, recall, and F1 score.

💡 Hint: Use the respective formulas for each metric.

Challenge 2 Hard

Discuss the implications of a model with high accuracy but very low precision. What corrective actions might you take?

💡 Hint: Consider the balance between finding positives and the risk of false positives.

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