[Retracted] Developing Countermeasures of Integrating Entrepreneurship Education with Professional Education in Colleges and Universities Using Data Mining

Table 1

Basic structure of DT.

Component name	Component function
Node 1	Input point of data, the “root” of DT
“Yes” or “no”	Details of the amount of data inside the node and the number of “yes” + “no” equals the total amount of data inside the node.
Node 3, node 5, and node 6	The leaf node of the DT can predict the future trend of the same situation.
“Age <42.5.”	The split condition can judge and segment the data when the data decision attribute values are different to construct the DT further.