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- Title
一种新型的自适应多核学习算法.
- Authors
聂逯松; 常方圆; 常学智; 刘 畅; 金有为; 刘国晟; 付加胜; 韩霄松
- Abstract
Aiming at the problem of the training data set with large samples, high dimension, and complex features, a self-adaptive multiple kernel learning algorithm was proposed by integrating support vector machine with ant colony optimization algorithm. The affinity propagation clustering algorithm was used to find the similar features adaptively, and then the parameters of the kernel function were selected adaptively by ant colony algorithm, so as to select the optimal kernel function quikly. Experimental results of five groups of UCI data sets show that the proposed algorithm has higher classification accuracy and F1 value than the traditional support vector machine, which verifies the effectiveness and feasibility of the proposed algorithm.
- Subjects
ANT algorithms; SUPPORT vector machines; ALGORITHMS; KERNEL functions; KERNEL operating systems; MACHINE learning
- Publication
Journal of Jilin University (Science Edition) / Jilin Daxue Xuebao (Lixue Ban), 2021, Vol 59, Issue 5, p1212
- ISSN
1671-5489
- Publication type
Article
- DOI
10.13413/j.cnki.jdxblxb.2021045