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This article mainly introduces the relevant knowledge of python how to achieve random forest, the content is detailed and easy to understand, the operation is simple and fast, and has a certain reference value. I believe you will gain something after reading this python article on how to achieve random forest. Let's take a look at it.

Background introduction

Random forest is a trademark term for a group of decision trees. In random forests, we collect decision trees (also known as "forests"). In order to classify new objects based on attributes, each tree has a classification, which we call "voting" for this class. The forest chooses the category with the most votes (on all trees in the forest).

The planting and growth of each tree is as follows:

If the number of cases in the training set is N, then N case samples are randomly selected, but need to be replaced. The sample will become a training set for tree growth.

If there are M input variables, specify the number m

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