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基于生物启发式算法的微阵列基因数据多类分类方案。

A Bio-inspired Algorithm based Multi-class Classification Scheme for Microarray Gene Data.

机构信息

Department of Computer Science, St. Pius X College, Kasaragod, Kerala, India.

PG and Research Department of Information Technology, Government Arts College, Coimbatore, India.

出版信息

J Med Syst. 2019 May 29;43(7):208. doi: 10.1007/s10916-019-1353-y.

Abstract

Microarray gene data is widely known for its high dimensionality and volume. The utilization of microarray gene data is increasing now-a-days, owing to the advancement of medical science. Microarray gene data helps in diagnosing diseases quite accurately. However, processing microarray gene data is difficult and is usually not understandable. Taking this challenge into account, this work presents a user-friendly rule based classification model, which is easily understandable and does not demand users to have prior knowledge. The classification rules are formed with the help of cuckoo search optimization algorithm and the rules are pruned by the associative rule mining. Finally, the classification is performed with the help of the pruned rules. The performance of the proposed approach is satisfactory in terms of accuracy, sensitivity, specificity and time consumption.

摘要

微阵列基因数据以其高维度和大容量而广为人知。由于医学科学的进步,现在越来越多地利用微阵列基因数据。微阵列基因数据有助于非常准确地诊断疾病。然而,处理微阵列基因数据很困难,通常不容易理解。考虑到这一挑战,本工作提出了一个用户友好的基于规则的分类模型,该模型易于理解,不需要用户具有先验知识。分类规则是在布谷鸟搜索优化算法的帮助下形成的,并且规则是通过关联规则挖掘进行修剪的。最后,利用修剪后的规则进行分类。就准确性、灵敏度、特异性和时间消耗而言,所提出的方法的性能令人满意。

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