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5 cards from this section. Quick, good the night before a test.
What is boosting in machine learning?
Think about how teams work together to improve.
Name one popular boosting algorithm.
Consider the names of algorithms discussed.
What does boosting aim to achieve in machine learning?
Think about the goal of joining multiple models together.
AdaBoost assigns more weight to which of the following?
Consider which instances help improve the model most.
Explain how boosting can lead to overfitting in certain scenarios. Provide an example.
Consider situations where complex models are problematic.
Design an experiment comparing the effectiveness of AdaBoost and XGBoost on a real-world dataset of your choosing.
Think about what metrics best indicate performance.
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