计算机工程与应用2012，Vol.48Issue(20)：172-176,5.DOI:10.3778/j.issn.1002-8331.2012.20.036
不完备数据下的免疫分类算法
Immune classification algorithm under incomplete data
摘要
Abstract
Artificial Immune Recognition System (AIRS) that is inspired by natural immune system has been developed as an efficient classifier. But the number of memory cells is too large and the accuracy of AIRS is not high, especially in the case of incomplete data. To solve the problem, this paper presents Immune Classification Algorithm Under (ICAU) incomplete data. It introduces semi-supervised learning, classifier fusion and vote to decision ideas, uses multiple AIRS classifiers to learn to refine each other. In the UCI data sets, experimental results prove the validity of the ICAU algorithm.关键词
人工免疫系统/不完备数据/分类Key words
artificial immune/ incomplete data/ classification分类
信息技术与安全科学引用本文复制引用
舒才良,严宣辉,曾庆盛..不完备数据下的免疫分类算法[J].计算机工程与应用,2012,48(20):172-176,5.基金项目
福建省高校科研专项重点项目(No.JK2009006) （No.JK2009006）
福建省高校服务海西建设重点项目. （）
