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In the last decades, Robust Principal Component Analysis (PCA) has been drawn much attention in the image processing, computer vision and machine learning communities and various robust PCA methods have been developed. This paper introduces a new generalized robust PCA with emphasizing on ℓ2, 1-norm minimization on loss function. The ℓ2, 1-norm instead of Frobenius norms based loss function is robust...
There are relevance and redundancy of the feature words in the text vector space, so we proposed a text-reducing method based on the improved KNN algorithm in this paper. Vector polymer theory and feature selection methods were used to reducing the dimension of vector space. Feature words would have more ability to represent categories after feature selection. Experiments proved, the improved KNN...
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