Multilayered perceptron (MLP) network trained by recursive least squares algorithm
Dzati Athiar Ramli, Junita Mohamad–Saleh, Fakroul Ridzuan Hashim, Nor Ashidi Mat Isa · 2005
In my research, the performance of multilayered perceptron (MLP) network which trained by recursive least square (RLS) algorithm is investigated. The network has been implemented to classify the cervical cells into normal, low-grade squamos intraepithelial lesion(LSIL) and high-grade squamos intraepithelial lesion(HSIL). Based on Bathesda System, it has achieved to classify the cervical cells with high accuracy, sensitivity and specificity as well as lower false negative and false positive but more work should be done to enhance the system accuracy.