Figure 6.

Comparison of different variable selection methods for the same classification algorithm. For each of the classification algorithms (LDA, QDA, SVM, NB), identical number of genes are selected for each cancer dataset by BMSF and 11 other variable selection criteria (the number of genes used is according to BMSF). The LOOCV accuracy is presented in the dotplot, in which the coordinate of a point in the horizontal axis indicates the accuracy. A point located to the right represents higher accuracy than a point located to the left. In most of the cases, the algorithms with variables selected by BMSF reach the highest LOOCV accuracy. For the GCM data, the variables selected by the eight criteria from RankGene and MaxRel cannot perform QDA due to rank deficiency. So the average accuracy for QDA is calculated over the other datasets for fair comparison.

Zhang et al. BMC Bioinformatics 2012 13:298   doi:10.1186/1471-2105-13-298
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