Practice Evaluation Metrics for NLP - 9.8 | 9. Natural Language Processing (NLP) | Data Science Advance
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the formula for calculating accuracy?

💡 Hint: Think about how many predictions your model made correctly.

Question 2

Easy

Define precision in the context of model evaluation.

💡 Hint: Focus on how many positive predictions were actually correct.

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 the accuracy of a model indicate?

  • The proportion of correct predictions
  • The number of true positives
  • The overlap of n-grams

💡 Hint: Consider the total predictions made.

Question 2

True or False: A high precision score always indicates a good model.

  • True
  • False

💡 Hint: Think about the balance between precision and recall.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

A classification model returns 100 total predictions: 80 true positives, 10 false positives, and 10 false negatives. Calculate the precision, recall, and F1-score.

💡 Hint: Use the formulas for precision, recall, and F1-score provided in class.

Question 2

Consider a machine translation output with a BLEU score of 0.65. If the reference translation had an n-gram overlap of 60%, discuss whether this is an acceptable score and why.

💡 Hint: Evaluate the BLEU score compared to industry standards.

Challenge and get performance evaluation