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Impact of Feature Selection on Support Vector Machine Using Microarray Gene Expression Data

机译：利用微阵列基因表达数据的特征选择对支持向量机的影响

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Recent researches have investigated the impact of feature selection methods on the performance of support vector machine (SVM) and claimed that no feature selection methods improve it in high dimension. However, they have based this argument on their experiments with simulated data. We have taken this claim as a research issue and investigated different feature selection methods on the real time micro array gene expression data. Our research outcome indicates that feature selection methods do have a positive impact on the performance of SVM in classifying micro array gene expression data.

机译：最近的研究已经研究了特征选择方法对支持向量机（SVM）性能的影响，并声称没有任何特征选择方法可以在高维度上对其进行改进。但是，他们是基于对模拟数据的实验而得出的。我们已将此主张作为研究课题，并研究了实时微阵列基因表达数据的不同特征选择方法。我们的研究结果表明，在对微阵列基因表达数据进行分类时，特征选择方法确实对SVM的性能产生积极影响。

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《Machine Vision, 2009. ICMV '09》|2009年|189-193|共5页
会议地点 Dubai(AE);Dubai(AE)
作者
Wahid Choudhury Muhammad Mufassil; Ali A.B.M. Shawkat; Tickle Kevin;
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关键词
Cancer Classification; Feature selection; Microarray Gene expression data; Support Vector Machine;

机译：癌症分类;特征选择;微阵列基因表达数据;支持向量机;

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专利

1. A HYBRID OF GENETIC ALGORITHM AND SUPPORT VECTOR MACHINE FOR FEATURES SELECTION AND CLASSIFICATION OF GENE EXPRESSION MICROARRAY [J] . MOHD SABERI MOHAMAD, SAFAAI DERIS, ROSLI MD ILLIAS International Journal of Computational Intelligence and Applications . 2005,第1期

机译：基因表达微阵列特征选择和分类的混合遗传算法和支持向量机
2. Feature selection and tumor classification for microarray data using relaxed Lasso and generalized multi-class support vector machine [J] . Kang Chuanze, Huo Yanhao, Xin Lihui, Journal of Theoretical Biology . 2019,第期

机译：使用轻松的套索和广义多级支持向量机进行微阵列数据的特征选择和肿瘤分类
3. A multiple kernel support vector machine scheme for feature selection and rule extraction from gene expression data of cancer tissue [J] . Zhenyu Chen, Jianping Li, Liwei Wei Artificial intelligence in medicine . 2007,第2期

机译：从癌症组织的基因表达数据中进行特征选择和规则提取的多核支持向量机方案
4. Impact of Feature Selection on Support Vector Machine Using Microarray Gene Expression Data [C] . Choudhury Muhammad Mufassil Wahid, A. B. M. Shawkat Ali, Kevin Tickle International Conference on Machine Vision . 2009

机译：特征选择对支持向量机的影响使用微阵列基因表达数据
5. Network-based support vector machines for classification of microarray gene expression data [D] . Zhu, Yanni 2009

机译：基于网络的支持向量机，用于微阵列基因表达数据的分类
6. sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic [O] . Pijush Das, Anirban Roychowdhury, Subhadeep Das, 2020

机译：sigFeature：使用支持向量机和t统计量对基因表达数据进行分类的重要特征选择方法
7. Classification of cancer data based on support vectors machines with feature selection using genetic algorithm and Laplacian score [O] . Z. Rustam, I. Primasari, D. Widya 2018

机译：基于支持向量机器的癌症数据分类使用遗传算法和拉普拉斯评分的特征选择

Impact of Feature Selection on Support Vector Machine Using Microarray Gene Expression Data

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