This article starts with the importance of electric power marketing
systems, introduces the technical characteristics of data mining and its
application status in electric power marketing systems, thereby
providing decision-making basis for the economic operation of power
grids. And propose using C5.0 decision tree algorithm to deeply analyze
the marketing data of the electric power marketing management system.
The original C5.0 decision tree algorithm is improved by introducing
information entropy, which improves its classification speed and
accuracy. Experimental results on UCI machine learning dataset and power
marketing dataset show that the proposed improved C5.0 decision tree
algorithm has good classification performance and can meet the
classification and prediction requirements in power marketing work.
Decision tree induction is one of the useful approaches for extracting classification knowledge from a set of feature-based instances. The most popular heuristic information used in the decision tree generation is the minimum entropy. This heuristic information has a serious disadvantage-the poor generalization capability [3]. Support Vector Machine (SVM) is a classification technique of machine learning based on statistical learning theory. It has good generalization. Considering the relationship between the classification margin of support vector machine(SVM) and the generalization capability, the large margin of SVM can be used as the heuristic information of decision tree, in order to improve its generalization capability.This paper proposes a decision tree induction algorithm based on large margin heuristic. Comparing with the binary decision tree using the minimum entropy as the heuristic information, the experiments show that the generalization capability has been improved by using the new heuristic.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.