Additional file 8: of The parameter sensitivity of random forests

AUC results for high p/n data. Validation results for all high p/n models (n = 1000) using the MSKCC data, DFCI data, and combined MSKCC and DFCI data. The AUC results and ranks are provided for each combination of n tree , m try and sampsize parameters. Lower ranks represent higher model performance with 1 representing the most accurate model and 1000 representing the worst performing model. Logical columns are present to indicate whether a parameter set performed better than the default or well across all validation sets. Model performance was defined as good if the parameter set resulted in an AUC of > 0.6 across all validation sets. The default settings (n tree  = 500, m try  = 110, sampsize = 255) are found on row 596 of the table. (CSV 28 kb)