Cloud-service decision tree classification for education platform

摘要

Aiming at the NP hard problem existed in the university students' ideological education, this paper puts forward an optimization algorithm for the university students' ideological education based on the cloud-service decision tree classification algorithm. Firstly, it researches the ideological education model of university students, puts forward the optimized objective function and constraint of the university students' ideological education and establishes the optimized mathematical model, besides, it provides the multi-objective weight self-adaptation form; Secondly, it introduces the cloud-service decision tree classification algorithm, aiming at the problem that the fixed domain hunting scope of traditional cloud-service decision tree classification algorithm is not beneficial to enhance the algorithm hunting efficiency, to enhance the evolution efficiency of algorithm; finally, based on comparison experiment, it verifies the effectiveness of the algorithm, meanwhile, conducts systematic design on the algorithm in optimizing the university students' ideological education. (C) 2018 Elsevier B.V. All rights reserved.