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As a conclusion, the contribution of this paper is constructing a new simple nearest neighbor architecture to deal with imbalanced classification effectively without any manually parameter coordination, and further expanding the family of the nearest neighbor based rules.
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So the LSROPC can help improve the classification accuracy effectively.
In multi-label learning, the key to successful classification is effectively exploiting the complex correlations among the output labels.
Experimental results showed that KPCA feature extraction and the SVM classification algorithm effectively distinguished four statuses of through-wall human being detection and achieved the desired results.
Thus, the proposed classification tree effectively establishes a relation between the cell bandwidth and congestion issues: a high contribution of the classes related to congestion suggests that there is a lack of extra bandwidth.
Because Bayesian classification can effectively account for data uncertainty, it can be used in the setting of missing data, as commonly occurs in large, population-based registries such as the one chosen for this study.
Study results indicate baseline Support scores, in addition to other factors such as marital status and sapropterin response classification, could effectively predict long-term attrition within our PKU study cohort.
The present chemotaxonomic classification could be effectively used for Rhodiola species identification.
The established chemotaxonomic classification could be effectively used for Rhodiola species identification.
Deep neural network (DNN) is developed based on deep learning theory, which can enhance the accuracy of big data classification [33] and effectively overcome the preceding shortcomings.
This paper presents a novel hyperspectral image (HSI) classification method to effectively exploit the 3D spectral-spatial information via superpixel-based 3D deep neural networks (3D DNNs).
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