Association Rules Enhanced Classification of Underwater Acoustic Signal

Classification of underwater acoustic signal is one of the important fields of pattern recognition. Inspired by the experience of training man experts in sonar, we propose a two-phase training algorithm to exploit the association rules to reveal the understandable intrinsic rules contributing to correct classification in the known misclassification datasets in this paper. Preliminary experimental results demonstrate the potential of classification association rules to enhance the accuracy of classification of underwater acoustic signals.