Practice What Is Bias And Variance? (6.4.1) - Machine Learning Basics

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9 questions

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6 questions · about 4 min · pass mark 70%. Hints available.
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3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What is bias in machine learning?
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Think about how assumptions affect a model's performance.
Question 2.
What happens when a model has high variance?
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Consider how a model might react to noise in the dataset.
3Question 3.
What does high bias in a model lead to?
- Overfitting
- Underfitting
- Good performance
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Think about what happens when a model doesn't learn enough.
4Question 4.
True or False: High variance is always desirable in a model.
- True
- False
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Consider the draw of complexity vs. performance.
Question 5.
You are tasked with building a model to predict sales for a new product. Describe how you would approach addressing both bias and variance in your model design.
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Consider starting with basic features and then introduce new ones carefully.
Question 6.
A model shows excellent training accuracy but poor validation accuracy. Discuss the adjustments you’d implement to address high variance.
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Think about how you can reduce model complexity.

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