Ensemble LearningIt is the idea of combining multiple models into a high-precision model. It is mainly used in the field of machine learning. It is not a separate machine learning algorithm, but rather completes the learning task by building and combining multiple learners.
Ensemble learning can be used for classification problems, regression problems, feature selection, outlier detection, etc. It can be said that ensemble learning can be seen in all fields of machine learning.
There are currently two main problems that need to be solved in integrated learning:
- How to obtain several individual learners;
- If the individual learners are combined into a strong learner
References
【1】Summary of the Principles of Ensemble Learning (personal blog post)