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Selecting a feature subset with strong discriminative power is a critical process for high dimensional data analysis, which has attracted much attention in many application domains, such as text categorization and genome projects. Since traditional feature selection methods provide limited contributions to classification, many researchers resort to hybrid or elaborate approaches to choose interesting...
The nodules and the multiple times larger non-nodules of the regions of interested(ROIs) in lung areas are achieved, that would lead to a serious imbalance on the sample data. Many scholars have proposed some algorithms to solve this problem. In this paper, in order to guarantee that there is no correlation among the extracted characteristics, the PCA method is adopted to optimize and reduce dimensions,...
In recent research, classification involving imbalanced datasets has received considerable attention. Most classification algorithms tend to predict that most of the incoming data belongs to the majority class, resulting in the poor classification performance in minority class instances, which are usually of much more interest. In this paper we propose a clustering-based subset ensemble learning method...
With the availability of powerful multimedia edition software, all kinds of personalized image and video resources have flooded in the network. Multimedia forensics technology becomes a new topic in the field of information security. In this paper, a new source video system identification algorithm is proposed based on the features in the encoded stream; it takes full advantage of the different characteristics...
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