Developing New VO2max Prediction Models from Maximal, Submaximal and Questionnaire Variables Using Support Vector Machines Combined with Feature Selection

In this study, for the first time in the literature, we combine the triple of maximal, submaximal and questionnaire variables to propose new VO2max prediction models using Support Vector Machines (SVM ’s) combined with the Relief-F feature selector to predict and reveal the distinct predictors of VO2max. For comparison purposes, hybrid models based on double combinations of maximal, submaximal and questionnaire variables have also been developed.

Source: Computers in Biology and Medicine - October 19, 2016 Category: Bioinformatics Authors: Fatih Abut, Mehmet Fatih Akay, James George Source Type: research