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. |
Simpan untuk Revisi
Bookmark item ini, tandai sebagai sulit, atau masukkan ke dalam set revisi.
Masuk untuk menyimpan bookmark, pertanyaan sulit, dan set revisi.
Apakah ini membantu? Ya Tidak
Most helpful rated by users:
- Explain the concept of feature engineering.
- What is the purpose of regularization in machine learning?
- Explain the term \'hyperparameter\' in the context of machine learning.
- What is the purpose of the activation function in a neural network?
- Explain the term \'precision\' in the context of classification.