Intelligent Course Plan Recommendation for Higher Education: A Framework of Decision Tree

Algorithm 2

C4.5: decision tree construction algorithm

Input: evaluation matrix , where is the training sample set and is the attribute set.

Output: decision tree .

1 initial as a root node with the whole sample in and attribute in ;

2 for each leaf node in with and do

3  if or ,belongs to a same categorythen

4   stop and output ;

5

6  else

7   1. calculate the information gain ratio for all attributes about ;

8   2. select with as the category test attribute about node ;

9    for eachtest attributedo

10    construct a branch labeled with the attribute value;

11   end

12

13  end

14 end