----------------------------------------README-------------------------------------------------

* k-NN (KNearestNeigbhor.py)
	1. Enter the name of the input data file in the file variable
               	    file_name=’project3_dataset1.txt’ or ‘project3_dataset2.txt’
	2. Enter the value of the k (nearest neighbor)
	3. K-folds is specified as 10

* Naive Bayes (NaiveBayes.py)
      	1. Enter the name of the input data file in the file variable
                	    file_name=’project3_dataset1.txt’ or ‘project3_dataset2.txt’
      	2. K-folds is specified as 10

* Decision Tree (decisiontree.py)
	1. Enter the name of file in the filename variable 
 	    file_name= 'project3_dataset1.txt'
      	2. K-folds is specified as 10
               	    k_folds=10

* Random Forest (RANDOMFOREST.py)
                  1. Enter the name of file in the filename variable 
	    file_name= 'project3_dataset1.txt'
                  2. K-folds is specified as 10
               	     k_folds=10
                  3. Enter the number of trees to be built
                	    no_of_trees=6

* Boosting (Boost.py)
	1.  Enter the name of file in the filename variable 
      	     file_name= 'project3_dataset1.txt'
	2. K-folds is specified as 10
      	     k_folds=10
	3. Enter the number of trees to be built
      	    no_of_trees=6