计算机科学 ›› 2010, Vol. 37 ›› Issue (9): 209-211.
• 人工智能 • 上一篇 下一篇
严超,王元庆
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YAN Chao,WANG Yuan-qing
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摘要: 现阶段的人工智能与模式识别工作中,连续型Adaboost算法以其良好的识别率和极快的识别速度得到了越来越多的应用。鉴于此,认真研究了连续型Adaboost算法的理论基础,细致分析了基于连续型Adaboost算法的分类器的训练流程,对算法中涉及到的数学量之间的关系进行了探讨,对算法中涉及到的数学过程进行了定量推导,对训练过程中出现的问题的成因进行了定性分析,最后对如何提高连续型Adaboost算法的性能提出了若干建议。
关键词: 连续型Adaboost算法,PCA模型,归一化因子,检测率,过学习现象
Abstract: In the current artificial intelligence and pattern recognition, Real Adaboost Algorithm, as for high accuracy rate and very fast specd,has been used more widely. As a result, we researched the theoretical basis of the Real Adaboost Algorithm conscientiously and analyzed the training procedures of classifiers based on the Real Adaboost Algorithm meticulously. In this course, we probed into the relationship between the mathematical variables involved in the algorithm; deduced the mathematical process involved in the algorithm quantitatively, and analyzed the reasons of problems appearing in training procedures qualitatively. At last, in order to improve the Real Adaboost Algorithm, we brought up several suggestions.
Key words: Real Adaboost algorithm, PCA model, Normalization factor, Testing rate, Excessive learning
严超,王元庆. 连续型Adaboost算法研究[J]. 计算机科学, 2010, 37(9): 209-211. https://doi.org/
YAN Chao,WANG Yuan-qing. Research of the Real Adaboost Algorithm[J]. Computer Science, 2010, 37(9): 209-211. https://doi.org/
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