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| 摘要: |
| 根据基因表达谱数据的特点，提出了全局分量模型(global component model，简称GCM)和癌症组分量模型(cancer component model，简称CCM)两种癌症识别模型。结合GCM模型和CCM模型的互补性，利用基于权值的投票组合策略提出一种基于组合GCM和CCM的癌症分类算法(ensemble algorithm based on GCM and CCM for cancer recognition，简称EAGC)。在Leukemia，Breast，Prostate，DLBCL |
| 关键词: 基因表达谱 癌症识别 全局分量模型 癌症组分量模型 |
| DOI： |
| 分类号: |
| 基金项目:Supported by the National Natural Science Foundation of China under Grant No.60873184 (国家自然科学基金); the National Science Foundation for Post-Doctoral Scientists of China under Grant No.20100471790 (国家博士后科学基金); the Hu’nan Provincial Natural Science Foundation of China under Grant No.07JJ5085 (湖南省自然科学基金) |
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| Classification Algorithm Combined GCM with CCM in Cancer Recognition |
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LU Xin-Guo, Lin Ya-Ping, Luo Jia-Wei, Li Dan
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| Abstract: |
| In this paper, two cancer recognition models, global component model (GCM) and cancer component model (CCM), are constructed. Due to the fact that GCM and CCM complement each other, a weighted voting strategy is applied, and an ensemble algorithm based on GCM and CCM for cancer recognition (EAGC) is proposed. Independent test experiments and cross validation experiments are conducted on Leukemia, Breast, Prostate, DLBCL, Colon, and Ovarian cancer dataset, respectively, and EAGC performed well on all datasets. The experimental results show that recognition, solution, and the generalization are strengthened by the combination of GCM and CCM. |
| Key words: gene expression profile cancer recognition global component model cancer component model |
