Artur Oliveira Rodrigues ; artur [at] dcc.ufmg.br

The documentation (in Portuguese) is located in the doc directory, and the reference file is doc/tp2.pdf.

The algorithm was implemented in Python and its code can be found at k_means.py. Additional code is also located in the file utils.py.

The way the k-Means algorithm was implemeted allows the tuning of multiple parameters, as follows:

positional arguments:
  -i, --input           observations file
  -k, --num_of_clusters number of clusters

optional arguments:
  -c, --centroids_file  file contaning user-specified initial centroids
  -d, --debug           display debug information
  -h, --help            show this help message and exit

Here is a sample parameters configuration:

$ python k_means.py -i data/lfm.dat -k 3

and here is the sample output (simplified for clarity):

0 2
1 2
2 0
3 2
4 2
(...)
4995 1
4996 1
4997 1
4998 1
4999 1