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Model selection is one of the key issues both in recent research and application of kernel methods. Cross-validation is a commonly employed and widely accepted model selection criterion. However, it requires multiple times of training the algorithm under consideration, which is computationally intensive. In this paper, we present a novel strategy for(More)
Kernel selection is one of the key issues both in recent research and application of kernel methods. This is usually done by minimizing either an estimate of generalization error or some other related performance measure. It is well known that a kernel matrix can be interpreted as an empirical version of a continuous integral operator, and its eigenvalues(More)
Active search is a learning paradigm with the goal of actively identifying as many members of a given class as possible. Many real-world problems can be cast as an active search, including drug discovery, fraud detection, and product recommendation. Previous work has derived the Bayesian optimal policy for the problem, which is unfortunately intractable due(More)
OBJECTIVE To investigate the diagnostic value of different detection methods for Mycobacterium tuberculosis in bronchoalveolar lavage fluid (BALF) from patients with pulmonary tuberculosis.
 Methods: BALF from100 patients in Changsha Central Hospital from January 2013 to December 2015 was collected. Among 100 patients, 65 cases were clinically diagnosed as(More)
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