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What is the main advantage of using ensemble methods in supervised learning?
What is the main advantage of using ensemble methods in supervised learning?
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Practice Questions
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What is the main advantage of using ensemble methods in supervised learning?
They are simpler to implement
They reduce the risk of overfitting
They combine predictions from multiple models to improve accuracy
They require less data for training
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Ensemble methods combine predictions from multiple models, which often leads to improved accuracy and robustness.
Questions & Step-by-step Solutions
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Q
Q: What is the main advantage of using ensemble methods in supervised learning?
Solution:
Ensemble methods combine predictions from multiple models, which often leads to improved accuracy and robustness.
Steps: 4
Show Steps
Step 1: Understand that ensemble methods use more than one model to make predictions.
Step 2: Learn that by combining the predictions from these models, we can get a better overall prediction.
Step 3: Recognize that using multiple models helps to reduce errors and improve accuracy.
Step 4: Realize that ensemble methods can make predictions more reliable and robust against different types of data.
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