Page 137 - Data Science Algorithms in a Week

Clustering into K Clusters

0.4011627907), 4), ((0.125, 1.0), 2), ((0.625, 0.0058139535), 3), ((1.0,
0.0), 1), ((0.5, 0.0058139535), 3), ((0.375, 0.0174418605), 3), ((0.5,
0.0174418605), 3), ((0.75, 0.0174418605), 3)]
centroids = [(0.0, 0.0406976744), (1.0, 0.0), (0.125, 1.0), (0.5,
0.0174418605), (0.25, 0.3430232558)]
Step number 1: point_groups = [((0.0, 0.0406976744), 0), ((0.0,
0.0988372093), 0), ((0.125, 0.0581395349), 0), ((0.0, 0.1860465116), 0),
((0.0, 0.0348837209), 0), ((0.0, 0.1569767442), 0), ((0.0, 0.0348837209),
0), ((0.25, 0.3430232558), 4), ((0.25, 0.261627907), 4), ((0.125,
0.4011627907), 4), ((0.125, 1.0), 2), ((0.625, 0.0058139535), 3), ((1.0,
0.0), 1), ((0.5, 0.0058139535), 3), ((0.375, 0.0174418605), 3), ((0.5,
0.0174418605), 3), ((0.75, 0.0174418605), 3)]
centroids = [(0.017857142857142856, 0.08720930231428571), (1.0, 0.0),
(0.125, 1.0), (0.55, 0.0127906977), (0.20833333333333334,
0.3352713178333333)]

This clustering further divides the blue cluster of the remaining religious books into the
blue cluster of the Hindi books and the gray cluster of the Christian books.

[ 125 ]