optimizing classification using Neural Net
I am using fuzzy input as my input data to neural net. The input neurons are fuzzy members. The output consists of 2 labels. I am just getting the classification accuracy as 83%, as oppose to the 98% accuracy obtained by the author of proposed paper. Can any one tell me how can i increase the accuracy. My input neurons are 74, output neurons are 2 , hidden neurons are 50. my training data consists of 630 records and testing data of 70 records.
Please help me.
Please help me.