Wrapper to calculate performance metrics (Mathews correlation coefficent, sensitivity and specificity) for each model for each response variable.

mrIMLperformance(yhats, model1, X, model = "regression")

Arguments

yhats

A list is the list generated by mrIMLpredicts

model1

A list #the model used to generate the yhats object

X

A dataframe #is a response variable data set (specie, SNPs etc).

Details

Outputs a dataframe of commonly used metric that can be used to compare model performance of classification models. Performance metrics are based on testing data. But MCC is useful (higher numbers = better fit)