Question

In C++ program a simple k-means clustering algorithm, kmeans, using the Euclidean distance for 2-dimensional numerical data. Your program should be executed as follows: kmeans k input.txt where input parameter k > 1 is an integer, specifying the number of clusters. input.txt is an input file containing many 2-dimensional data points in the following format,

274 119

317 144

267 164

233 137

272 99

297 116

268 142

522 286

468 308

441 263


Your program should output a txt file called output.txt, in the following format:
274 119 1

317 144 1

267 164 1

233 137 1

272 99 1

297 116 1

268 142 1

522 286 2

468 308 2

441 263 2

In output.txt, 1 and 2 are cluster labels. Each data point should be labeled using one of the labels from 1 to k. In the above example, there are 10 data points and k = 2

Answer 1

def EuclideanDistance(x, y):
   S = 0;
   for i in range(len(x)):
       S += math.pow(x[i]-y[i], 2);

   return math.sqrt(S);