Regularized Label Relaxation Linear Regression

IEEE Transactions on Neural Networks and Learning Systems(2018)

引用 95|浏览103
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摘要
Linear regression (LR) and some of its variants have been widely used for classification problems. Most of these methods assume that during the learning phase, the training samples can be exactly transformed into a strict binary label matrix, which has too little freedom to fit the labels adequately. To address this problem, in this paper, we propose a novel regularized label relaxation LR method,...
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关键词
Training,Manifolds,Learning systems,Linear regression,Algorithm design and analysis,Closed-form solutions,Computer science
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