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4 cards from this section. Quick, good the night before a test.
What is the primary purpose of ensemble methods?
Think about the impact of combining models on biases and variances.
What does Bagging stand for?
Consider how this method relates to sampling.
What technique combines multiple models to achieve better performance?
Think about how companies often use multiple forecasts.
True or False: Bagging is effective at reducing bias.
Focus on what each term aims to address.
Given data about house prices, construct a scenario where using an ensemble method is more beneficial than using a single model. Explain your reasoning.
Consider how different models might capture various patterns in the pricing data.
Analyze the impact of overfitting in ensemble model performance. Provide an example where this could significantly affect decisions.
Think about the balance between model complexity and performance on unseen data.
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