6.3.2 - Evaluation Metrics
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Practice Questions
Test your understanding with targeted questions
Define 'accuracy' in the context of classification metrics.
💡 Hint: Think about the correct predictions made by a model.
What does the confusion matrix display?
💡 Hint: Visualize how a model performs on different classifications.
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Interactive Quizzes
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What is precision in classification metrics?
💡 Hint: Think about false positives in the definition.
True or False: Mean Squared Error is always less than Mean Absolute Error for any dataset.
💡 Hint: Consider the nature of squaring the errors.
2 more questions available
Challenge Problems
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A telecom company wants to assess if their model for predicting customer churn is effective. After implementing the model, the confusion matrix reveals 70 true positives (churn correctly predicted), 30 false positives (predicted churn but retained), 10 false negatives (churn not predicted), and 90 true negatives (correct retention). Calculate accuracy, precision, recall, and F1 Score.
💡 Hint: Make sure to apply the formulas for each metric.
Imagine you are tasked with modeling housing prices using regression metrics. If your predictions yield an MAE of 2000 and an MSE of 5000000, illustrate why it is beneficial to check both metrics rather than relying on just one.
💡 Hint: Think of the implications of errors in pricing and their impact on business.
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