kmeans_test

kmeans_test, an Octave code which calls kmeans(), which handles the K-Means problem, which organizes a set of N points in M dimensions into K clusters;

Licensing:

The computer code and data files described and made available on this web page are distributed under the MIT license

Related Data and Programs:

kmeans, an Octave code which contains several different algorithms for the K-Means problem, which organizes a set of N points in M dimensions into K clusters;

Source Code:

• kmeans_test.m, calls all the tests.
• kmeans_test.sh, runs all the tests.
• kmeans_test.txt, the output file.

• kmeans_test01.m, tests HMEANS_01.
• kmeans_test02.m, tests HMEANS_02.

There are data files read by the sample code:

• points_100.txt, 100 2D points, used as a case study by the sample problem.
• points_100.png, an image of the points.
• ruspini.txt, 75 points in 2D, with integer coordinates, and 0 < X < 120, 0 < Y < 160, which might naturally be grouped into 4 sets.
• ruspini.png, an image of the points.
• weights_equal_100.txt, 100 equal weights, for doing equally weighted calculations when a program expects weights.
• weights_unequal_100.txt, 100 weights, not all equal, for testing programs that can use weights.

TEST01 applies HMEANS_01 to points_100.txt:

• test01_clusters.txt the cluster assignments.
• test01_centers.txt the cluster centers.

TEST02 applies HMEANS_02 to points_100.txt:

• test02_clusters.txt the cluster assignments.
• test02_centers.txt the cluster centers.

TEST03 applies KMEANS_01 to points_100.txt:

• test03_clusters.txt the cluster assignments.
• test03_centers.txt the cluster centers.

TEST04 applies KMEANS_02 to points_100.txt:

• test04_clusters.txt the cluster assignments.
• test04_centers.txt the cluster centers.

TEST05 applies KMEANS_03 to points_100.txt:

• test05_clusters.txt the cluster assignments.
• test05_centers.txt the cluster centers.

TEST06 applies HMEANS_01 + KMEANS_01 to points_100.txt:

• test06_clusters.txt the cluster assignments.
• test06_centers.txt the cluster centers.

TEST07 applies HMEANS_01 + KMEANS_02 to points_100.txt:

• test07_clusters.txt the cluster assignments.
• test07_centers.txt the cluster centers.

TEST08 applies KMEANS_01 + KMEANS_03 to points_100.txt:

• test08_clusters.txt the cluster assignments.
• test08_centers.txt the cluster centers.

TEST09 applies HMEANS_W_01 to points_100.txt and weights_equal_100.txt:

• test09_clusters.txt the cluster assignments.
• test09_centers.txt the cluster centers.

TEST10 applies HMEANS_W_02 to points_100.txt and weights_equal_100.txt:

• test10_clusters.txt the cluster assignments.
• test10_centers.txt the cluster centers.

TEST11 applies KMEANS_W_01 to points_100.txt and weights_equal_100.txt:

• test11_clusters.txt the cluster assignments.
• test11_centers.txt the cluster centers.

TEST12 applies KMEANS_W_03 to points_100.txt and weights_equal_100.txt:

• test12_clusters.txt the cluster assignments.
• test12_centers.txt the cluster centers.

TEST13 applies HMEANS_W_01 to points_100.txt and weights_unequal_100.txt:

• test13_clusters.txt the cluster assignments.
• test13_centers.txt the cluster centers.

TEST14 applies HMEANS_W_02 to points_100.txt and weights_unequal_100.txt:

• test14_clusters.txt the cluster assignments.
• test14_centers.txt the cluster centers.

TEST15 applies KMEANS_W_01 to points_100.txt and weights_unequal_100.txt:

• test15_clusters.txt the cluster assignments.
• test15_centers.txt the cluster centers.

TEST16 applies KMEANS_W_03 to points_100.txt and weights_unequal_100.txt:

• test16_clusters.txt the cluster assignments.
• test16_centers.txt the cluster centers.