## Table 3 |
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Simulation Example 3 |
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False patterns |
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Methods |
X_{100} |
X_{200} |
X_{300}X_{400} |
X_{150}X_{450}X_{451} |
(Variables) |

pLPS3 | 47 (50) | 50 (50) | 47 (50,50) | 47 (50,49,48) | 204 |

Logic | 50 (50) | 50 (50) | 34 (43,44) | 30 (50,44,41) | 151 |

RF | NA (50) | NA (50) | NA (36,40) | NA (49,47,49) | (279) |

SPLR | 50 (50) | 50 (50) | 45 (49,50) | 50 (50,50,50) | 554 |

*n *= 1000 and *p *= 500, 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