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Multi-label learning plays a critical role in the areas of data mining, multimedia, and machine learning. Although many multi-label approaches have been proposed, few of them have considered to de-emphasize the effect of noisy features in the learning process. To address this issue, this paper designs a new method named representative multi-label learning algorithm. Instead of considering all features,...
Multi-view learning, one of the important sub-fields in the area of machine learning, has gained more and more attention in class prediction of gene expression datasets. In this paper, we propose a new classifier ensemble framework, named as multi-view based Ad-a boost classifier ensemble framework (MV-ACE), which not only utilizes a random view generation technique to regulate different views and...
Human interaction is one of the most important characteristics of group social dynamics in meetings. In this paper, we propose an approach for capture, recognition, and visualization of human interactions. Unlike physical interactions (e.g., turn-taking and addressing), the human interactions considered here are incorporated with semantics, i.e., user intention or attitude toward a topic. We adopt...
Protein phosphorylation is an important step in many biological processes, such as cell cycles, membrane transport, apoptosis, etc. In order to obtain more useful information about protein phosphorylation, it is necessary to develop a robust, stable, and accurate approach to predict phosphorylation sites. Although there exist a number of approaches to predict phosphorylation sites, such as those based...
Given the essential role of protein in life processes, computational assignment of protein functions has become one of the most important tasks in the area of bioinformatics. While Gene Ontology (GO) has been widely used in functional annotation, new approaches to address the problem of annotation incompleteness, which can leverage the support of the GO framework, are imminently required. In this...
Protein phosphorylation is an important step in many biological processes, such as cell cycles, membrane transport, apoptosis, and so on. We design a new classifier ensemble approach called Bagging-Adaboost Ensemble (BAE) for the prediction of eukaryotic protein phosphorylation sites, which incorporates the bagging technique and the adaboost technique into the classifier framework to improve the accuracy,...
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