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Several computational methods have been proposed to assess the quality of tandem mass spectra. These methods range from supervised to unsupervised algorithms, discriminative to generative models. Unsupervised learning algorithms for tandem mass spectra are not probabilistic model based and they don't provide probabilities for spectra quality assessment. In this study, the distribution of high quality...
In the literature, hundreds of features have been proposed to assess the quality of tandem mass spectra. However, some features may be nearly irrelevant, and thus the inclusion of these nearly irrelevant features may degenerate the performance of quality assessment. This paper introduces a two-stage support vector machine recursive feature elimination (SVM-RFE) method to select the most relevant features...
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