CAF É-Map: Context Aware Feature Mapping for mining high dimensional biomedical data

Feature selection and ranking is of great importance in analysis of biomedical data. In addition to reducing the number of features used in classification or other machine learning tasks, it allows us to extract meaningful biological and medical information from a machine learning model. Most existing approaches in this domain do not directly model the fact that the relative importance of features can be different in different regions of the feature space. In this work, we present a context aware feature ranking algorithm called CAF É-Map.

Source: Computers in Biology and Medicine - October 10, 2016 Category: Bioinformatics Authors: Fayyaz ul Amir Afsar Minhas, Amina Asif, Muhammad Arif Source Type: research