Exploring a novel method for face image gender Classification using Random Forest and comparing with other Machine Learning Techniques
Amjath Fareeth Basha, Gul Shaira, Banu Jahangeer · 2014
Gender classification such as classifying human face is not only challenging for computer, but even hard for human in some cases. This Paper use ORL database contain 400 images include both Male and Female Gender. Our experimental results show the superior performance of our approach to the existing gender classifiers. We achieves excellent classification (100%) accuracy using approach (Continuous wavelet Transform and Random Forest) and compared with other classification Technique like Support Vector Machine, linear discriminate analysis, k- nearest neighbor, Fuzzy c – means, Fuzzy c – means.