| 一种基于KNN的半监督分类改进算法 |
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| 引用本文： | 陆广泉,谢扬才,刘星,张师超.一种基于KNN的半监督分类改进算法[J].广西师范大学学报(自然科学版),2012,30(1):45-49. |
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| 作者姓名： | 陆广泉 谢扬才 刘星 张师超 |
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| 作者单位： | 广西师范大学 计算机科学与信息工程学院,广西桂林,541004 |
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| 摘 要： | 本文提出一种新的基于KNN分类的半监督学习self-training改进算法,并以多个UCI数据集为实验,对基于KNN的半监督分类模型算法进行改进,充分利用已知类别标签数据的正确知识进行自训练,以得到最终分类结果.实验结果表明,该方法能显著提高分类准确率.
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| 关 键 词： | 半监督学习 KNN分类器 自训练 |
An Improvement Semi-supervised Learning Based on KNN Classification |
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| LU Guang-quan
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XIE Yang-cai
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LIU Xing
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ZHANG Shi-chao.An Improvement Semi-supervised Learning Based on KNN Classification[J].Journal of Guangxi Normal University(Natural Science Edition),2012,30(1):45-49. |
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| Authors: | LU Guang-quan XIE Yang-cai LIU Xing ZHANG Shi-chao |
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| Institution: | (College of Computer Science and Information Technology,Guangxi Normal University,Guilin Guangxi 541004,China) |
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| Abstract: | An improved semi-supervised self-training classification learning algorithm is proposed based on K nearest neighbor,and several UCI data sets are used for experiments to improve the KNN-based semi-supervised classification model(self-training model) algorithm.The labeled data which gives the correct knowledge from the training is provided to get the final classification results.And the results show that the method can increase the classification accuracy dramatically. |
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| Keywords: | semi-supervised learning KNN classification self-training |
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