Linear decision fusions in multilayer perceptrons for breast cancer diagnosis
Yunfeng Wu, Jinming Zhang, Cong Wang, Sin-Chun Ng · 2005
We introduce a non-parametric linear decision fusion called perceptron average (PA) for breast cancer diagnosis. We concretely compare the accuracy between both two fusion strategies for breast cancer diagnosis. The PA fusion demonstrates a higher overall diagnostic accuracy versus the weighted average fusion, and the PA fusion method also exhibits a better capability of generalization when a casualty of training data sizes. Moreover, the PA fusion gains a larger area covered by its receiver operating characteristic curve.