Recall & Review
beginner
What is the error rate in machine learning?
The error rate is the percentage of wrong predictions made by a model compared to the total predictions. It shows how often the model makes mistakes.
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beginner
Why is failure analysis important in machine learning?
Failure analysis helps us understand why a model makes mistakes. It identifies patterns or reasons behind errors so we can improve the model.
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beginner
How do you calculate the error rate from predictions?
Error rate = (Number of wrong predictions) ÷ (Total predictions). For example, if 10 out of 100 predictions are wrong, error rate = 10%.
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intermediate
What is a common method to perform failure analysis?
A common method is to look at the confusion matrix to see which types of errors happen most, then analyze those cases to find causes.
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intermediate
How can failure analysis improve a machine learning model?
By finding error patterns, we can fix data issues, adjust model settings, or add features. This reduces errors and makes the model better.
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What does a high error rate indicate about a model?
Which tool helps identify types of errors in classification?
What is the first step in failure analysis?
If a model has 5 wrong predictions out of 50, what is the error rate?
How can failure analysis help improve a model?
Explain what error rate means and how you calculate it.
Describe the steps and purpose of failure analysis in machine learning.