智能启发算法在机器学习中的应用研究综述

Survey of research on application of heuristic algorithm in machine learning

针对机器学习算法在应用中存在的问题,构建基于智能启发算法的机器学习模型优化体系。首先,介绍已有智能启发算法类型及其建模过程。然后,从智能启发算法在机器学习算法中的应用,包括神经网络等参数结构优化、特征优化、集成约简、原型优化、加权投票集成和核函数学习等方面说明智能启发算法的优势。最后,结合实际需求展望智能启发算法及在机器学习领域的发展方向。

Aiming at the problems existing in the application of machine learning algorithm,an optimization system of the machine learning model based on the heuristic algorithm was constructed.Firstly,the existing types of heuristic algorithms and the modeling process of heuristic algorithms were introduced.Then,the advantages of the heuristic algorithm were illustrated from its applications in machine learning,including the parameter and structure optimization of neural network and other machine learning algorithms,feature optimization,ensemble pruning,prototype optimization,weighted voting ensemble and kernel function learning.Finally,the heuristic algorithms and their development directions in the field of machine learning were given according to the actual needs.