require(pROC)
require(plotly)
require(MiMIR)
require(foreach)
require(ggplot2)
#load the dataset
m <- synthetic_metabolic_dataset
p<- synthetic_phenotypic_dataset
#Calculating the binarized surrogates
b_p<-binarize_all_pheno(p)
#Apply a surrogate models and plot the ROC curve
sur<-calculate_surrogate_scores(m, p, MiMIR::PARAM_surrogates, bin_names=colnames(b_p))
p_avail<-colnames(b_p)[c(1:5)]
LOBOV_accuracies(sur$surrogates, b_p, p_avail, MiMIR::acc_LOBOV)
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