Yunsong Qi

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An important application of gene expression data is to classify samples in a variety of diagnostic fields. However, high dimensionality and a small number of noisy samples pose significant challenges to existing classification methods. Focused on the problems of overfitting and sensitivity to noise of the dataset in the classification of microarray data, we(More)
In spite the fact that compatibility relation and similarity relation consider 'do not care' data as lost data, they were introduced to rough set to deal with incomplete information system. Incomplete information system in which 'do not care' data coexists with lost data, this article studies characteristic relation and discusses the unreasonable state(More)
Microarrays allow researchers to examine the expression of thousands of genes simultaneously. However, identification of genes differentially expressed in microarray experiments is challenging. With an optimal test statistic, we rank genes and estimate a threshold above which genes are considered to be differentially expressed genes (DE). This overcomes the(More)
This paper proposes a progressive sparse representation-based classification algorithm using local discrete cosine transform (DCT) evaluation to perform face recognition. Specifically, the sum of the contributions of all training samples of each subject is first taken as the contribution of this subject, then the redundant subject with the smallest(More)
In this paper, a novel classifier is proposed to classify microarray data using principal curves. Principal curves are the non-linear generalization of principal components. Intuitively, a principal curve ‘passes through the middle of the data cloud’. As a kind of new classification technique, Principal Curve-based classifier (PC) involves a novel way of(More)
Xin Shu 1,2,3,*, Qianni Zhang 3, Jinlong Shi 1 and Yunsong Qi 1 1 School of Computer Science & Engineering, Jiangsu University of Science & Technology, Zhenjiang 212003, China; jlshifudan@gmail.com (J.S.); mailqys@163.com (Y.Q.) 2 School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China 3 School of Electronic Engineering and(More)