k-means and linear regression analysis using java

.[login to view URL] a K - means high level algorithm and program for clustering the N-dimensional data point in your own language. The algorithm should be able to read the data from a data file that has data in the following form . Note: you can use software library for sorting if needed. Dimensions = <integer> <Tuple 1> <disease> <tuple 2> <disease> .... <tuple N> <disease> <Tuple> will be given as comma separated dimension coordinates starting from dimension 1. The dimension value will be given from 1..100. The <disease> will be a word for example ‘diabetes’, ‘kidney problem’, ‘acidity’ etc. If the <disease> column is missing, it would mean no disease is associated with that value. The distance measure will be Euclidean that means it is square root of squares of difference of coordinate and centeroids. Your program should display the coordinates of the centroid on the screen, the threshold value you gave, and the maximum distance from the centroid to the farthest point in a cluster for all the clusters. It should also give the coordinates of the 'Outliers' in a separate output file. Outliers are those points that do not belong to any [login to view URL] that there ay be more than one clusters for the same disease [login to view URL] a program for a linear regression analysis given a points in x - y Coordinates in a data file. You have to calculate the equation of the line, ovariance, variance(x - axis), variance(y - axis), and display the equation of the line, covariance , variances, and r - value. note: Generate your own test data . There must be aleast 100 data points and 4 clusters to demonstrate the program. All the cluster information and centroid Generation should be parameterized and not hardwired