Question

decision tree model​

Answer 1

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Answer 2

A decision tree is a machine learning algorithm that partitions the data into subsets. The partitioning process starts with a binary split and continues until no further splits can be made. Various branches of variable length are formed.

The goal of a decision tree is to encapsulate the training data in the smallest possible tree. The rationale for minimizing the tree size is the logical rule that the simplest possible explanation for a set of phenomena is preferred over other explanations. Also, small trees produce decisions faster than large trees, and they are much easier to look at and understand. There are various methods and techniques to control the depth, or prune, of the tree.

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