Approach to Eliminating Morbid Samples in Forward Neural Networks
Gan Cai · Journal of Jilin University · 2009
For efficiently eliminating morbid samples and improving the generalization ability of neural networks,we present an approach to eliminate morbid samples in forward neural networks based on the search thought and the Hamming distance,through developing the thought and introducing the distance.The approach can directly carry out searching and eliminating morbid samples,and do not consider prior knowledge,forms of samples,etc.Hence,its applicability is stronger.The results of numerical demonstration analysis show that the approach is scientific,effective and can effectively find out morbid samples of learning samples,it has obvious application value to solve problems of real world.