... Knowledge discovery(知识发现) Ensemble methods(集成方法) Machine learning theory and methods(机器学习理论和方法) ...
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Experimental results show that the proposed algorithm has better classification performance than single SVM. Compared with the traditional ensemble learning methods such as Bagging and Adaboost, this novel ensemble method also has better classification accuracy.
实验结果表明,该算法不仅具有明显优于单一支持向量机的分类性能,而且能取得比传统集成学习算法Bagging和Adaboost更高的分类正确率。
参考来源 - 基于离散化方法的支持向量机集成研究·2,447,543篇论文数据，部分数据来源于NoteExpress
Compared with the single suppo vector machine method, the support vector machine ensemble method has better classification accuracy.
模拟实验结果表明，该方法具有明显优于单一支持向量机的更高的分类准确率。
After analyzing the traditional clustering algorithms, the paper presents a new clustering ensemble method based on K-means to cluster data.
本文在分析传统聚类算法的基础上，提出了一种聚类融合算法。
Ensemble learning is a general method for classifying data streams.
对数据流分类分析的常用方法是集成学习。
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