Multi-class Classification Algorithm Based on Ensemble Learning and Hierarchical Structure
ZOU Quan1,2,3, SONG Li1, CHEN Wen-Qiang1 , ZENG Jian-Cang1, LIN Chen1,2
1.School of Information Science and Engineering, Xiamen University, Xiamen 361005 2.Shenzhen Research Institute, Xiamen University, Shenzhen 518057 3.School of Computer Science and Technology, Tianjin University, Tianjin 300072
Abstract：The classification algorithm is an important research field in data mining and pattern recognition. A multi-class classification algorithm based on ensemble learning and hierarchical structure is proposed. Firstly, the problems are decomposed according to their hierarchy categories. The hierarchical structure of the hierarchical classifier is defined. Then, multiple weak classifiers are integrated by ensemble learning methods based on the hierarchical structure. Thus, the classification process is completed. In the data mining competition of CCDM 2014, the proposed algorithm achieves the highest performance on several indexes, including average accuracy and F1-score. The results verify the feasibility on the classification problem.
邹权，宋莉，陈文强，曾建沧，林琛. 基于集成学习和分层结构的多分类算法*[J]. 模式识别与人工智能, 2015, 28(9): 781-787.
ZOU Quan , SONG Li , CHEN Wen-Qiang , ZENG Jian-Cang , LIN Chen. Multi-class Classification Algorithm Based on Ensemble Learning and Hierarchical Structure. , 2015, 28(9): 781-787.
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