关键词: AdaBoost算法, 属性组合, 集成学习, 分类器组合

Abstract: Concerning the classification of samples being composed of digital attributes, an ensemble learning algorithm based on linear combination of samples attributes was proposed. It constructed classifiers based on combined attributes instead of single attribute by traditional AdaBoost algorithm. The general construction idea for attribute combination coefficients was put forward. In accordance with the idea, several concrete construction methods for combination coefficients were given and analyzed to be scientific and reasonable. The experimental results on UCI machine learning dataset illustrate that the ensemble learning algorithm based on attribute combination is effective and outperforms AdaBoost algorithm.

Key words: AdaBoost algorithm, attribute combination, ensemble learning, classification combination