Abstract

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.