Question: Differentiate between bagging and boosting.Answer: Bagging (Bootstrap Aggregating) and boosting are ensemble learning techniques. Bagging builds multiple models independently and combines them, while boosting builds models sequentially, giving more weight to misclassified instances. |
Is it helpful?
Yes
No
Most helpful rated by users:
- Explain the concept of feature engineering.
- Explain the term \'hyperparameter\' in the context of machine learning.
- What is the purpose of the activation function in a neural network?
- What is the purpose of regularization in machine learning?
- What is the concept of a confusion matrix?