General performance of mOPLS-DA using four datasets.
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Features were selected from the training set to fit OVRSVM models using the individual feature selection method. Observations of the training and independent test sets were classified and predicted by the corresponding fitted model, and the number of misclassified observation was counted. Key: athe number of features was optimized from 100 to 300 with the step of 10 and set to 160; b OVR, one-versus-rest; c KW, Kruskal–Wallis non-parametric one-way ANOVA; d cluster analysis.
创建时间：
2013-12-30
