On the study of nearest neighbor algorithms for prevalence estimation in binary problems

► Quantification is focused on the prediction of the prevalence of the positive class. ► We establish a new approach for quantification based on nearest neighbor algorithms. ► Our proposal offers competitive performance while balancing simplicity and effectiveness. ► We propose an evaluation methodology for quantification based on Friedman-Nemenyi test.