Special clustering method is used in our project to make use of spectral graph structure for partition of affinty matrix.
Affinity matrix is a weighted adjacency matrix of the data .project explain the effective approach to reduce or minimize the local
and global noises. We have used MULTIPLE KERNAL LEARNING (MKL) to extract local and global noises. To solve the
optimization method block coordinate descent algorithm is used in this project. It is Unsupervised Robust multiple kernal lerning
approach Unsupervised approach is done manually so it will decrease the chance of inaccuracy. It does not work on the preset
condition. work accordingly given condition.