Naive Bayes classification algorithm based on optimized training data | |
Zhu, Xiaodan ; Su, Jinsong ; Wu, Qingfeng ; Dong, Huailin ; Su JS(苏劲松) ; Wu QF(吴清锋) ; Dong HL(董槐林) | |
2012 | |
关键词 | Algorithms Classifiers Intelligent materials Optimization |
英文摘要 | Conference Name:2nd International Conference on Mechatronics and Intelligent Materials 2012, MIM 2012. Conference Address: GuiLin, China. Time:May 18, 2012 - May 19, 2012.; Naive Bayes classification algorithm is an effective simple classification algorithm. Most researches in traditional Naive Bayes classification focus on the improvement of the classification algorithm, ignoring the selection of training data which has a great effect on the performance of classifier. And so a method is proposed to optimize the selection of training data in this paper. Adopting this method, the noisy instances in training data are eliminated by user-defined effectiveness threshold, improving the performance of classifier. Experimental results on large-scale data show that our approach significantly outperforms the baseline classifier. 漏 (2012) Trans Tech Publications, Switzerland. |
语种 | 英语 |
出处 | http://dx.doi.org/10.4028/www.scientific.net/AMR.490-495.460 |
出版者 | Trans Tech Publications |
内容类型 | 其他 |
源URL | [http://dspace.xmu.edu.cn/handle/2288/85772] ![]() |
专题 | 软件学院-会议论文 |
推荐引用方式 GB/T 7714 | Zhu, Xiaodan,Su, Jinsong,Wu, Qingfeng,et al. Naive Bayes classification algorithm based on optimized training data. 2012-01-01. |
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