ABSTRACT
It is a big challenge to describe the accuracy of similar features in text document based on user requirements. Data classification is biggest issue in huge data sets. Fuzzy Relevance Feature Discovery Algorithm (FRFDA) is used to relevance feature discovery and it also classifies words in to different categories and updates that word weights in particular pattern. The testing result proves that, the proposed FRFDA is better than existing manual and automation methods. The data set Reuters-21578 shows that the proposed model significantly outperforms quicker and obtains better extracted quality than other methods.
