Fuzzy rough Neural Network Feature Selection
For the sake of measuring fuzzy uncertainty and rough uncertainty of real datasets,the fuzzy rough membership function(FRMF) defined in fuzzy rough set is introduced.A new fuzzy rough neural network(FRNN) is constructed based on neural network implementation of FRMF.FRNN has the merits of quick learning and good classification performance.A new neural network feature selection algorithm based on FRNN is designed.The input nodes are pruned according to the descent of accuracies and at the same time the search of optimal feature subset is realized.The test results on UCI datasets show that the algorithm is quick and effective,and has better selection precision and generalization ability than RBF feature selection.