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4 cards from this section. Quick, good the night before a test.
What is the main purpose of regularization in XGBoost?
Think about how we can simplify models.
Describe what tree pruning means in the context of XGBoost.
Consider how you would streamline something that has extra parts.
What types of regularization does XGBoost support?
Remember the definitions of L1 and L2.
True or False: XGBoost handles missing values by requiring preprocessing for imputation.
Think about how XGBoost's efficiency benefits users.
Explain how both L1 and L2 regularization in XGBoost can be strategically used. Provide a hypothetical scenario where you would favor one over the other.
Consider a scenario where feature elimination would either help or hinder performance.
Critique the impact of parallel processing on model training time compared to traditional sequential processing in algorithms. Discuss potential downsides.
Analyze both the advantages and challenges of using parallel processing.
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