THE ROLE OF P-SELECTIN IN THE FORMATION AND DEVELOPMENT OF CHRONIC KIDNEY DISEASE AND THE CREATION OF PREDICTIVE MATHEMATICAL MODELS

Abstract

Random forests are somewhat interpretable, as they return feature values that can be used to compare the most useful variables for making predictions. Random forests are generally very accurate and perform well on nonlinear problems with many features, as they perform implicit feature selection.