Classification and Progression Based on CFS-GA and C5.0 Boost Decision Tree of TCM Zheng in Chronic Hepatitis B

Algorithm 2

The general description of decision tree.

Input node 𝑛, Dataset 𝐷, partitioning method of 𝐹_𝑛();

Output Decision tree on node 𝑛 as its root node, Dataset 𝐷 and partitioning method of 𝐹_𝑛();

(1) Procedure Build Tree

(2)  Initialization root node 𝑛

(3)   Find decision feature 𝑛 according to 𝐹_𝑛 on Dataset 𝐷

(4)   If node 𝑛 meets with conditions of partition

(5)   According to decision feature, Partition Dataset 𝐷

     into 𝐷1 and 𝐷2, and creates two subnodes of 𝑛, namely 𝑛1

     and 𝑛2;

(6)  Build Tree (𝑛1, 𝐷1, 𝐹_𝑛);

(7)   Build Tree (𝑛2, 𝐷2, 𝐹_𝑛);

(8)  End if

(9) End procedure