ABSTRACT

Aiming at the problem of data classification in enterprise cloud data, this article proposes a data classifier based on Particle Swarm Optimisation and Kernel Function Extreme Learning Machine (PSO-KELM) is proposed. PSO is utilised to get optimal parameters and the parameters of KELM are obtained accurately, which improves the accuracy of data classification. Through the cloud data test and a comparison with Kernel Function Extreme Learning Machine (KELM), Kernel Function Support Vector Machine (KSVM) and Semi-Supervised and Transfer Learning (SSTL), the better classification effect is obtained. Moreover, this article proposes an effective method for data classification.

摘要

针对企业云数据中的数据分类问题，提出了一种基于粒子群优化和核函数极限学习机（PSO-KELM）的数据分类器。利用粒子群优化算法得到最优参数，准确得到KELM的参数，提高了数据分类的准确性。通过云数据测试，并与核函数极限学习机（KELM）、核函数支持向量机（KSVM）和半监督迁移学习（SSTL）进行比较，得到了较好的分类效果。此外，本文提出了一种有效的数据分类方法。