Practice Cost Function (log Loss / Cross-entropy) (5.2.3) - Supervised Learning - Classification Fundamentals (Weeks 5)
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Cost Function (Log Loss / Cross-Entropy)

Practice - Cost Function (Log Loss / Cross-Entropy)

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does Log Loss measure in a classification model?

💡 Hint: Consider the aspect of prediction confidence.

Question 2 Easy

Why can't we use Mean Squared Error in Logistic Regression?

💡 Hint: Think about how it affects local minima.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary function of Log Loss in a classification model?

To minimize prediction errors
To measure confidence in predictions
To evaluate model bias

💡 Hint: Consider how it affects classification.

Question 2

True or False: Using Mean Squared Error as a cost function for Logistic Regression is advisable.

True
False

💡 Hint: Think about the optimization process.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a model predicts probabilities for 100 instances, with actual outcomes of 60 ones and 40 zeros, calculate the total Log Loss if each of the true labels matches perfectly with predicted probabilities.

💡 Hint: Consider how Log Loss functions for perfect predictions.

Challenge 2 Hard

Discuss how you would approach optimizing a logistic model's parameters if the Log Loss displays high values. What steps would you take?

💡 Hint: Think about what factors could affect predictive accuracy.

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Reference links

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