Very simplified implementation of some traditional algorithms in PR. Just help those taking the relevant modules better understand the algorithms. Methods Implemented: 1.Linear discriminant function 2.Batch Perceptron Learning algorithm 3.Sequential Perceptron Learning algorithm 4.Sequential Multiclass Perceptron Learning algorithm 5.MSE via Pseudoinvers 6.Widrow-Hoff Learning Algorithm 7.k-nearest-neighbour classifier 8.Sequential Delta learning rule with H linear threshold 9.Negative feedback network 10.Fisher's evaluation of LDA 11.Singular Value Decomposition 12.Batch Oja's Rule 13.Extreme Learning 14.Sparse Coding 15.Adaptive Boost (Not formal) 16.SVM