Implement the linear classifier learning algorithms -> Batch Perceptron , Ho-Kashyap using pseudo inverse

perform n-fold cross-validation on each dataset. i.e., divide the dataset into n non-overlapping partitions (using the splitDataset() function) andin each fold, test using one of the folds while training using the other n-1.

Output : Report the average error, standard deviation of error and the confusion matrix.

compile : make run : ./a.out ip1 = Dataset File ip2 = Algorithm ( 1 for Batch Perception and 2 for Ho-Kashyap) ip3 = Combination ( 1 for 1vsRest and 2 for 1 vs 1 Majority Voting)