关键词: 混淆矩阵, 支持向量机（SVM）, 集成学习, AdaBoost

Abstract:

For the multiclassification problem, a classification method based on confusion matrix and ensemble learning is proposed in this paper. A hierarchical structure is generated from the similarities between patterns. The classification method chooses support vector machine (SVM) as the basic binary classifier. The AdaBoost algorithm applies weighted voting on SVM whose classification accuracy is not ideal. Taking object recognition in the substation environmental monitoring as an example (related to people, animals, ordinary flames (red and yellow flames), white flames, incandescent lamps), object classification is achieved. The experiments show that the proposed method can effectively improve the classification accuracy.

Key words: confusion matrix;support vector machine(SVM);ensemble learning;AdaBoost