| 基于维数约简与特征选择的PGS方法在数据处理中的应用 |
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| 引用本文： | 程辉,卜华龙. 基于维数约简与特征选择的PGS方法在数据处理中的应用[J]. 数字社区&智能家居, 2007, 0(23) |
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| 作者姓名： | 程辉 卜华龙 |
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| 作者单位： | 滁州学院,计算机科学与技术系,安徽,滁州,239000 巢湖学院,计算机科学与技术系,安徽,巢湖,238000 |
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| 摘 要： | 特征选择和维数约简在机器学习、模式识别和数据挖掘领域是很常用的方法,它们之间也具有一定的联系,但对它们的融合应用目前很少研究,从而融合特征选择和维数约简的思路被提出.该思路融合了主成分分析方法和遗传算法,提出PGS方法,并把它应用于基因microarray数据的预测分类,取得了较好的效果.
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| 关 键 词： | 特征选择 维数约简 遗传算法 主成分分析 基因矩阵 |
PGS Based on Dimension Reduction and Feature Selection for Microarray Data |
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| CHENG Hui,BU Hua-Long. PGS Based on Dimension Reduction and Feature Selection for Microarray Data[J]. Digital Community & Smart Home, 2007, 0(23) |
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| Authors: | CHENG Hui BU Hua-Long |
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| Affiliation: | CHENG Hui1,BU Hua-Long2 |
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| Abstract: | Feature selection and dimension reduction are two common methods for Machine Learning,Pattern Recognition and Data Mining,and they have many relations,but there are little attention about how to fusion them,so the method of fusing the feature selection and dimension reduction is proposed.The method fused the Genetic Algorithm and Principal Component Analysis(PGS) ,then used it for the classification of gene microarray data. |
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| Keywords: | Feature selection Dimension reduction Genetic Algorithm Principal component Analysis gene matrix |
| 本文献已被 CNKI 维普 等数据库收录！ |
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