分类树是一种目标变量为固定或类别型的算法。该算法随后被用于识别目标变量最有可能落入的“类别”。

分类型问题的一个例子是确定谁会或不会订阅数字平台;或者谁会或不会从高中毕业。

这些是简单的二元分类示例,其中类别型因变量只能取两个互斥值中的一个。在其他情况下,您可能需要在多个不同变量之间进行预测。例如,您可能需要预测消费者会决定购买哪种类型的智能手机。

在这种情况下,类别型因变量有多个值。以下是经典的分类树示例:



A classification tree is an algorithm where the target variable is fixed or categorical. The
algorithm is then used to identify the “class” within which a target variable would most likely fall.
An example of a classification-type problem would be determining who will or will not subscribe to a
digital platform; or who will or will not graduate from high school.
These are examples of simple binary classifications where the categorical dependent variable can
assume only one of two, mutually exclusive values. In other cases, you might have to predict among a
number of different variables. For instance, you may have to predict which type of smartphone a
consumer may decide to purchase.
In such cases, there are multiple values for the categorical dependent variable. Here’s what a classic
classification tree looks like

最后修改: 2025年06月19日 星期四 10:19