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What is the main advantage of using ensemble methods in supervised learning?
Practice Questions
Q1
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
Questions & Step-by-Step Solutions
What is the main advantage of using ensemble methods in supervised learning?
Steps
Concepts
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.
No concepts available.
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