Additional file 7 of Systematic interrogation of mutation groupings reveals divergent downstream expression programs within key cancer genes

Additional file 7: Figure S6. Increasing computational complexity does not change or improve upon classification performance. We observed similar subgrouping classification performance in METABRIC(LumA) when we repeated our prediction tasks with (a) a support vector machine classifier and (b) a random forest classifier in place of the logistic ridge regression classifier that was originally used. (c) Using these more computationally complex classifiers did not result in improved classification performance across all non-random classification tasks, nor did tuning using a greater number of potential hyper-parameter values.