Application of decision tree construction algorithm based on decision classify-entropy
Xingqi Wang · Journal of Computer Applications · 2009
In order to better complete the task of classification mining on financial datasets,decision classify-entropy concept was put forward based on the rough set theory; and based on this concept,a novel decision tree construction algorithm was proposed. To overcome over-fitting,inhibiting factor was introduced to control decision tree construction. The case study and experimental results in financial datasets show that,compared with the classical C4.5 algorithm,the new algorithm can resolve the drawbacks of the traditional algorithm and could construct a suboptimal decision tree effectively. The application in financial field also proves that the new algorithm can finish the objective task much better.