Gender Classification Based on Human Radiation Wave Analysis

Abstract

This paper describes an analysis of body radiation frequency for the purpose of gender classification. The human radiation frequency is experimentally studied from 33 healthy human subjects of 17 males and 16 females. KNN classifier is employed for gender classification. The number of training to testing ratio was evaluated at 50 to 50, 60 to 40 and 70 to 30, to determine best classification accuracy. The data was analyzed separately of raw dataset and post-processing dataset to compare the classification results. At first, the data was classified using raw dataset and yields the classification accuracy of 93.8%. Then, the post-processing data was applied to the classifier, and it was found that the classification accuracy was improved to perfect classification on k = 5, 7, 11 and 13 to 15.