README

1. knn_bayesian_demo.m		- show how a naive bayesian classier will classify the Fisher's Iris data. 
				- show how K-nearest neighbors will classify the Iris dataset 
3. tools/knn.m	 	- implementation of K-nearest neighbors algorithm
4. tools/divideset.m	- devides a dataset into training and testing dataset. See Chapter 2's tools 
5. plotgauss1D.m	- plots gausian curve (mu, sigma2) 
5. plotgauss2D.m	- plots gausian curve (mu1, std1, mu2, std2, numberOfStd) 

Any question, comments, or reccomendations 
please email to georgiev@temple.edu