Constraint-based semi-supervised dimensionality reduction with conflict detection

Most existing typical semi-supervised learning algorithms focused on the results of learning while facing the conflict on constraints. And most solutions use unsupervised distance-based methods to adjust the conflicting constraints on the information by recalculating the samples' distance. This...

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Bibliographische Detailangaben

Hauptverfasser:	Binhui Chen, Qingyuan Bai
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Accuracy adjustment of constraints Algorithm design and analysis Clustering algorithms clustering analysis conflict detection Data mining Machine learning semi-supervised learning Software SSDR Symmetric matrices
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