Man pages for GegznaV/manyROC
Tools for ROC Analyis

access_elements[!] Access elements of roc_result_list object
add_class_labelManage S3 class labels
calculate_performancePerformance measures for two-class classification
cvo_create_foldsCreate a cvo (cross-valitation object)
cvo_get_infoAccess information in a cvo object
cvo_test_bs[+] Test if data in folds is stratified and blocked
fluorescenceDataset of simulated fluorescence spectra
get_var_valuesGet vector of variable values
manyROCManyROC - tools for ROC analysis
measure_kappaCohen's kappa
measure_wkappaWeighted Cohen's kappa
parallelSetSeedSet seeds for reproducible parallel computing with...
roc_analysisCarry out the ROC analysis
roc_extract_info[!!!] Extract the main information necessary for prediction
roc_manyrocCarry out the manyROC analysis
roc_manyroc_cvCarry out the manyROC analysis with cross-validation
roc_merge_manyroc_cv_resultsMerge 2 lists with manyROC CV results
roc_performance_measures[!!!] Performance measures
roc_predictPredict outcome for new data
roc_predict_performance_by_grCalculate perfornamce for each pair of groups
sp_manyroc_with_cvDo manyROC analysis with cross-validation for hyperSpec...
sp_manyroc_with_cv_by_variableDo manyROC analysis with cross-validation for hyperSpec...
GegznaV/manyROC documentation built on Oct. 3, 2017, 11:05 p.m.