Fuzzy Approach for pattern recognition using Classification Algorithms

Fuzzy Logic (FL) is a multivalve logic that allows intermediate values to be defined between conventional evaluations like true/false, yes/no, high/low, etc. Pattern Recognition is the study of how machines can observe the environment, learn to distinguish patterns of interest from their background, and make sound and reasonable decisions about the categories of the patterns.” Here we are using Supervised Classification (e.g. Discriminant Analysis) in which the input pattern is identified as a member of a predefined class and Unsupervised classification (e.g. clustering) in which the pattern is assigned to an unknown class.? In this paper we are applying Fuzzy K-NN and K-NN both are classification methods (i.e. Supervised Learning and unsupervised learning) and classes identified by patterns and classifies by the K- nearest neighbors, it also give the previous knowledge about the problem classes