| 对改进的联想记忆器的研究 |
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| 引用本文： | 高隽 曹先彬. 对改进的联想记忆器的研究[J]. 中国科学技术大学学报, 1999, 29(1): 96-100 |
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| 作者姓名： | 高隽 曹先彬 |
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| 作者单位： | 中国科学技术大学计算机科学与技术系 |
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| 摘 要： | 运用统计物理学的平均场理论来研究改进的联想记忆器问题。通过对三阶输出函数的有关网络状态的稳定性讨论，提出了一种对伪态的影响加以削弱的方法，并与Ｈｏｐｆｉｅｌｄ联想记忆网络进行了比较以及给出模拟结果来验证理论分析。
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| 关 键 词： | 平均场 联想记忆器 神经网络 稳定性 容错性 |
An Improved Naive Bayes Algorithn |
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| ZHANG Xiaoyin YUE Lihua. An Improved Naive Bayes Algorithn[J]. Journal of University of Science and Technology of China, 1999, 29(1): 96-100 |
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| Authors: | ZHANG Xiaoyin YUE Lihua |
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| Abstract: | Although Naive Bayes algorithm, which is based on the assumption that every attribute is independently given the class, is shown to be surprisingly accurate for some classification tasks, yet in some large databases, the accuracy of Naive Bayes doesn't scale up other complicated algorithms. An improved algorithm is thus proposed which join the attributes according to their degree of dependency. Experiments show that this new approach out performs Naive Bayes algorithm in many databases, especially in those areas where decision tree algorithm such as C4.5 performs well. |
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| Keywords: | artificial intelligence data mining naive bayes algorithm instance attributes |
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