Figure 5.
The impact of scale updating on efficiency, effectiveness and clustering hierarchy. (a and b) Running times of WFC with different
settings and scale-updating functions for the first 50 million taxi locations in the NYC dataset and the first 1000 images in the CASIA-webface dataset respectively, where the hyper-exponential function is
. (c) F1-measure of WFC with different
settings and scale-updating functions for the 1000 images. (d and e) Visualization of clustering hierarchy and statistical results for the 1000 images with different
settings. The radius of each brown circle (cluster) is proportional to the square root of the corresponding cluster size. For a clear visualization, each isolated data point
and the link to its parent cluster (the cluster containing
in the last scale) are not plotted.
