Table 2

Simulation Example 2
False patterns
Methods X500 X5000 X1000X3000 X7000X7002 (Variables)
pLPS 50 (50) 50 (50) 48 (48,50) 50 (50,50) 278
RF NA (50) NA (50) NA (28,37) NA (50,50) (335)
SPLR 50 (50) 50 (50) 50 (50,50) 50 (50,50) 800

n = 1000 and p = 8000, with correlations among neighboring variables. Tabulated numbers show the number of tests (out of 50) in which the pattern was detected by each algorithm. The number outside the parentheses is the number of times the given pattern was selected; the numbers inside the parentheses shows how many times the variables in the pattern are detected in the model, as a main effect or in some interaction. The final column shows the total number of times (in 50 tests) that the algorithms selected patterns (variables for RF) that are not in the true model.

Shi et al.

Shi et al. BMC Bioinformatics 2012 13:98   doi:10.1186/1471-2105-13-98

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