Title :
Pattern grouping strategy makes BP algorithm less sensitive to learning rate
Author :
Lu, Yingyang ; Xu, Shenchu ; Wu, Boxi ; Chen, Zhenxiang
Author_Institution :
Dept. of Phys., Xiamen Univ., China
Abstract :
In the normal backpropagation learning process, the whole set of target patterns is learned again and again. We think that, the pattern grouping strategy (PGS), in which the patterns to be learned are divided into subgroups and are learned subgroup by subgroup, may be helpful for the BP training process. The investigation of the affect of the learning rate on the success rate of the BP learning process with PGS may serve as a proof
Keywords :
backpropagation; feedforward neural nets; pattern recognition; learning rate sensitivity; pattern grouping strategy; success rate; target patterns; training process; Algorithm design and analysis; Expert systems; Humans; Jacobian matrices; Multidimensional systems; Neural networks; Physics; Sea surface; Shape; Switches;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.832642