A fuzzy-based data transformation for feature extraction to increase classification performance with small medical data sets

摘要

ObjectiveMedical data sets are usually small and have very high dimensionality. Too many attributes will make the analysis less efficient and will not necessarily increase accuracy, while too few data will decrease the modeling stability. Consequently, the main objective of this study is to extract the optimal subset of features to increase analytical performance when the data set is small.