Recall & Review
beginner
What is a learning curve in machine learning?
A learning curve is a graph that shows how a model's performance improves over time or with more training data. It helps us understand if the model is learning well or if it needs adjustments.
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intermediate
What does it mean if a learning curve shows high training accuracy but low validation accuracy?
This usually means the model is overfitting. It learns the training data too well but does not generalize to new data.
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intermediate
How can learning curves help decide if more training data is needed?
If the validation error continues to decrease as the training set size increases, it indicates that more training data would be beneficial.
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intermediate
What does a learning curve look like when a model is underfitting?
Both training and validation errors are high and do not improve much with more data or training, showing the model is too simple.
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beginner
Why is it useful to plot both training and validation learning curves?
Plotting both helps compare how well the model learns from training data and how well it generalizes to unseen data, guiding improvements.
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What does a learning curve typically plot?
If training error is low but validation error is high, what is likely happening?
What can you infer if both training and validation errors are high and close?
How can learning curves help improve a model?
What does a flat learning curve with high error indicate?
Explain what a learning curve is and how it helps in understanding model training.
Describe the differences in learning curves when a model is overfitting versus underfitting.