Text classification is the process of automatically sorting a set of documents into categories from a predefined set. Feature clustering is a powerful method to reduce the dimensionality of feature vectors for text classification. After pre-processing, the document can be clustered in the schema level based on the occurrence of the words relatively. Clustering process group the words based on the pattern. In proposing a feature clustering mechanism finds the pattern match with the number of relevant data present in the database.