This function returns the statistical metrics describing the association between model predictions and the ground truth outcome
predictionStats_binary(predictions, plotname="", center=FALSE,...)
predictionStats_regression(predictions, plotname="",...)
predictionStats_ordinal(predictions,plotname="",...)
predictionStats_survival(predictions,plotname="",...)A matrix whose first column is the ground truth, and the second is the model prediction
The main title to be used by the plot function. If empty, no plot will be provided
For binary predictions indicates if the prediction is around zero
Extra parameters to be passed to the plot function.
The classification accuracy with its95% confidence intervals (95/
The balanced error rate with its 95%CI
The ROC area under the curve (ROC AUC) of the binary classifier with its 95%CI
The specificity with its 95%CI
The sensitivity with its 95%CI
The output of the ROC function
The output of the epiR::epi.tests function
the Pearson correlation with its 95%CI
the regression bias and its 95%CI
the root mean square error (RMSE) and its 95%CI
the Spearman correlation and its 95%CI
the mean absolute difference(MAE) and its 95%CI
the output of the cor.test function
the Kendall correlation and its 95%CI
the ordinal regression bias and its 95%CI
the balanced mean absolute difference for ordinal regression
the output of the bootstrapped estimation of accuracy, sensitivity, and ROC AUC
the output of the DescTools::KendallTauB function
the output of the irr::kappa2 function
The follow-up concordance index with its95% confidence intervals (95/
The risks concordance index with its95% confidence intervals (95/
The LogRank test with its95% confidence intervals (95/
These functions will analyze the prediction outputs and will compare to the ground truth. The output will depend on the prediction task: Binary classification, Linear Regression, Ordinal regression or Cox regression.