中文说明：多分类器集成系统是当前机器学习领域的一个研究热点。由于使用多个基分类器构建的集成系统通常比单个优秀的分类器具有更强的泛化能力,因此多分类器集成系统为许多基于传统模式识别方法很难解决的分类问题提供了新的解决方案。DNA微阵列技术是一种由物理学、微电子学与分子生物学等几个领域综合交叉形成的高新技术,该技术已经在医学与生物学上得到越来越广泛的应用,其中在癌症分析检测上的应用使得在大规模基因水平上深入研究癌症的发生、扩散等病理特征成为可能。特别地,进行可靠的癌症类型诊断与预测、癌症关键基因的识别和癌症的分类已成为当前癌症研究中的两项重要内容。尽管如此,由于微阵列数据具有数据维数高、样本数少的特点,因而使用常规的模式识别方法并不能总是获得理想的结果。本文主要针对多分类器集成系统在基因微阵列数据集上的应用进行了深入的分析与探讨,并设计了新的集成系统,以更好地解决微阵列数据的分类判别问题。
English Description：
Multiple classifiers integrated system is currently a hot research topic in the field of machine learning. Due to the use of multiple base classifiers integrated system better than a single classifier usually have better generalization ability, multiple classifiers integrated system based on the traditional pattern recognition classification problem is difficult to solve for a new solution. DNA Microarray Technology is a kind of physics, microelectronics and molecular biology field intersecting a few forms of high technology, this technology has been more and more widely applied in medicine and biology, including application in cancer detection in large-scale gene research on the occurrence and spread of cancer pathology characteristics, such as possible. In particular, cancer types, cancer diagnosis and prediction of reliable identification of key genes and cancer classifications have become two important elements in the current cancer research. However, because they are micro-array d