关键词: 非相关线性判别分析, 支持向量机, 基因表达谱, 分类

Abstract: The classification of tissue samples based on gene expression data is an important problem in medical diagnosis of diseases.In gene expression data，the number of genes is usually very high（in the thousands） compared to the number of data samples（in the tens）；that is，the data dimension is large compared to the number of data points（such is undersampled problem）.Too high dimension（the number of features or genes） makes the task of classification quite challenging.This paper presents that ULDA and SVM are combined to classify colon tissue samples.Compared to other methods，the effect of classification is improved，the results prove the feasibility and effectiveness of this method.

Key words: Uncorrelated Linear Discriminant Analysis, SVM, gene expression profiling, classification