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.