Practice Accuracy - 5.3.2 | Module 3: Supervised Learning - Classification Fundamentals (Weeks 5) | Machine Learning
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5.3.2 - Accuracy

Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is accuracy in the context of a classification model?

💡 Hint: Think about the score relative to correct versus total predictions.

Question 2

Easy

What do TP and TN stand for?

💡 Hint: Consider these terms in relation to correctly identified cases.

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 accuracy measure in a classification model?

  • A: The proportion of predictions made correctly.
  • B: The total number of predictions made.
  • C: The average of true positives and true negatives.

💡 Hint: Remember what accuracy gauges in a model's performance.

Question 2

True or False: Accuracy can always be a reliable indicator of a model's effectiveness.

  • True
  • False

💡 Hint: Think about the impact of uneven class distribution.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Analyze a dataset where 95 out of 100 samples belong to the 'Class A' and only 5 samples belong to 'Class B'. If a model predicts all samples as 'Class A', what will be the accuracy and what does it indicate?

💡 Hint: Consider the implications of simply counting correct predictions without considering class balance.

Question 2

You are tasked with creating a pipeline for a classification model assessing rare disease presence. Discuss how you would evaluate model performance beyond accuracy.

💡 Hint: Role-play as a healthcare provider: How would you ensure all critical disease cases are identified?

Challenge and get performance evaluation