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
Statement III only
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
