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Questions and Answers
What is one consequence of fitting a hypothesis of high degree to a set of points?
What is one consequence of fitting a hypothesis of high degree to a set of points?
- Overfitting (correct)
- Optimal fitting
- Underfitting
- Converging
What is the main concern with overfitting in machine learning models?
What is the main concern with overfitting in machine learning models?
- Optimal prediction accuracy
- High bias
- Poor performance on unseen data (correct)
- Low variance
How can overfitting be reduced in machine learning models?
How can overfitting be reduced in machine learning models?
- By reducing the number of features (correct)
- By ignoring the training data
- By memorizing all training data points
- By increasing the complexity of the model
Which technique helps prevent overfitting by adding a penalty for complex models?
Which technique helps prevent overfitting by adding a penalty for complex models?
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What happens to prediction accuracy when a model overfits the training data?
What happens to prediction accuracy when a model overfits the training data?
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In machine learning, why is it important for a model to generalize well?
In machine learning, why is it important for a model to generalize well?
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What effect does high variance in a prediction curve have on a machine learning model's performance?
What effect does high variance in a prediction curve have on a machine learning model's performance?
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How does underfitting differ from overfitting in machine learning models?
How does underfitting differ from overfitting in machine learning models?
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What role does model complexity play in overfitting?
What role does model complexity play in overfitting?
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