首页    期刊浏览 2025年07月18日 星期五
登录注册

文章基本信息

  • 标题:PRINCIPAL COMPONENT ANALYSIS COMBINED WITH SECOND ORDER STATISTICAL FEATURE METHOD FOR MALARIA PARASITES CLASSIFICATION
  • 本地全文:下载
  • 作者:IIS HAMSIR AYUB WAHAB ; ADHI SUSANTO ; P. INSAP SANTOSA
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2014
  • 卷号:63
  • 期号:1
  • 出版社:Journal of Theoretical and Applied
  • 摘要:The main challenge in detecting malaria parasites is how to identify the subset of relevant features. The objective of this study was to identify a subset of features that are most predictive of malaria parasites using second-order statistical features and principal component analysis methods. Relevant features will provide the successful implementation of the overall detection modeling, which will reduce the computational and analytical efforts. The results showed that the combination of the principal components of the feature value the correlation to the ASM, and the contrast to the correlation can separate classes of malaria parasites.
  • 关键词:Features; PCA; Identify; Classification; Malaria
国家哲学社会科学文献中心版权所有