What is boosting in machine learning?
An example of an AI chatbot conversation about boosting in machine learning.
What is boosting in machine learning?
Boosting is an ensemble technique that combines multiple weak learners to create a strong predictive model.
How does boosting improve model accuracy?
Boosting improves accuracy by focusing on the errors of previous models, adjusting weights to correct them.
Can you give me an example of a boosting algorithm?
Sure! AdaBoost and Gradient Boosting are popular boosting algorithms used in various applications.
What are the advantages and disadvantages of using boosting?
Advantages include improved accuracy and robustness, while disadvantages can be overfitting and longer training times.
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