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View all- Deng HMeng XDeng FFeng L(2023)UNIT: A unified metric learning framework based on maximum entropy regularizationApplied Intelligence10.1007/s10489-023-04831-x53:20(24509-24529)Online publication date: 26-Jul-2023
Distance metric plays a significant role in machine learning methods(classification, clustering, etc.), especially in k-nearest neighbor classification(kNN), where the Euclidean distances are computed to decide the labels of unknown points. But ...
Adaptive distance metric learning based on the characteristics of data can significantly improve the learner’s performance. Due to the limitations of single metric learning for heterogeneous data, multiple local metric learning has become an ...
The performance of k-nearest neighbour classification highly depends on the appropriateness of distance metric designation. Optimal performance can be obtained when the distance metric is matched to the characteristics of data. Existing works on ...
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