Man pages for hexhead/privateEC
Privacy Preserving Evaporative Cooling Feature Selection and Classification with Relief-F and Random Forests

compileAndSaveAllResultsCompile the results of a simulation + classifier methods run
consensus_nestedCVConsensus nested cross validation for feature selection and...
createInteractionsCreate a differentially coexpressed data set with...
createMainEffectsCreate a simulated data set with main effects
createMixedSimulationCreate a data simulation with a mix of main and interaction...
createSimulationCreate a data simulation and return train/holdout/validation...
epistasisRankCompute and return epistasis rank scores
getImportanceScoresCompute and return importance scores (Relief-F scores)
originalThresholdoutOriginal Thresholdout algorithm
paperRealWorkflowRuns the four comparison algorithms on the passed correlation...
paperSimWorkflowWorkflow for running one simulation of the Bioinformatics...
plotRunResultsPlot the results of a privateEC workflow for a quick...
privateECPrivate Evaporative Cooling feature selection and...
privateEC-packageWelcome to privateEC
privateRFPrivate random forests algorithm
regular_nestedCVRegular nested cross validation for feature selection and...
rsfMRIcorrMDDAn MRI data set used used in the paper referenced below.
splitDatasetSplit a data set for machine learning classification
standardRFStandard random forests algorithm serves as a baseline model
xgboostRFxgboost random forests algorithm
hexhead/privateEC documentation built on July 20, 2018, 12:30 p.m.