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Pavel Korchagin · 2024年04月13日

CART的hyper parameter问题

NO.PZ2023040502000056

问题如下:

Which statement(s) best describe(s) the advantages of using Classification and Regression Trees (CART) instead of K-Nearest Neighbor (KNN)?

Statement I: For CART there is no requirement tospecify an initial hyperparameter (like K).

Statement II: For CART there is no requirement tospecify a similarity (or distance) measure.

Statement III: For CART the output provides a visualexplanation for the prediction.

选项:

A.

Statement I only

B.

Statement III only

C.

Statements I, II and III

解释:

C is correct. The advantages of using CART over KNN to classify companies into two categories (“not acquisition target” and “acquisition target”), include all of the following: For CART there are no requirements to specify an initial hyperparameter (like K) or a similarity (or distance) measure as with KNN, and CART provides a visual explanation for the prediction (i.e., the feature variables and their cut-off values at each node).

A is incorrect, because CART provides all of the advantages indicated in Statements I, II and III.

B is incorrect, because CART provides all of the advantages indicated in Statements I, II and III.

基础班里面说regularization parameters这一步要指定一些hyper parameter,这些不算是CART的hyper parameter吗

1 个答案

品职助教_七七 · 2024年04月13日

嗨,努力学习的PZer你好:


本题没有提到要对CART做regularization。

hyperparameter对于CART而言是可以有的,但并不是必须要有的。

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