| 基于逐步提取偏最小二乘主成分的特征选择方法 |
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| 引用本文： | 李建更,耿涛,阮晓钢.基于逐步提取偏最小二乘主成分的特征选择方法[J].生物学杂志,2010,27(4):85-87. |
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| 作者姓名： | 李建更 耿涛 阮晓钢 |
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| 作者单位： | 北京工业大学电子信息与控制工程学院人工智能与机器人研究所,北京,100124 |
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| 基金项目： | 北京市教育委员会科技计划项目，Beijing Natural Science Foundation |
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| 摘 要： | 特征选择技术被广泛应用于生物信息学中。通过重复利用偏最小二乘（partial least square,PLS）方法提取主成分,通过逐次选择在主成分中权重较大的基因,将PLS应用于特征选择中。将这种方法用于对肿瘤基因表达谱数据的特征基因选择中,并用提取的特征基因分类,用8个特征基因进行分类时,能达到92.5%的正确率。
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| 关 键 词： | 特征选择 偏最小二乘 主成分 肿瘤基因表达谱 |
Feature selection based on step-wise extraction of partial least square principal components |
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| LI Jian-geng,GENG Tao,RUAN Xiao-gang.Feature selection based on step-wise extraction of partial least square principal components[J].Journal of Biology,2010,27(4):85-87. |
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| Authors: | LI Jian-geng GENG Tao RUAN Xiao-gang |
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| Institution: | (Institute of Artificial Intelligence and Robotics,College of Electronic Information ＆ Control Engineering,Beijing University of Technology,Beijing 100124,China) |
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| Abstract: | Feature selection techniques are widely used in biological informatics.In this paper,partial least-squares（PLS） is repeatedly used for extracting principal components.By selecting the genes which have larger weights in principal components,PLS is introduced for feature selection.This method is used in tumor gene expression profiling data,and the feature genes selected is used for classification.Precision of 92.5% can be achieved when using 8 feature genes. |
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| Keywords: | feature selection partial least squares principal component tumor gene expression profiles |
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