Random forest of machine learning

【 brief introduction 】

Random forest is Bagging An extended variant of , It belongs to the integrated algorithm . The algorithm is simple to implement , Strong anti noise ability , The fitting phenomenon is not easy to occur , Therefore, it is widely used in many businesses .

1. Bagging

Need to master ：

• What is? Bagging
• Bagging How algorithms are trained and predicted

What is? Bagging

Bagging yes Bootstrap Aggregating English abbreviations , Beginners should not mistake Bagging It's an algorithm , Bagging and Boosting All are Integrated learning Medium Learning framework , Represents different ideas . And Boosting This serial ensemble learning algorithm is different , Bagging yes Parallel integrated learning Method . big-name Random forest algorithm Is in the Bagging Based on the modified algorithm .

Bagging Methodical The core idea Namely Two heads are better than one . If you use Bagging solve classification problem , Will be Multiple The result of the classifier Integrate Get up and do it vote , selection The highest number of votes As a result of final result . If you use Bagging solve