Open Access

Fig. 2


Download original image

Schematic of k-means algorithm, dots are training examples, and triangles are cluster centroids. (a) Original dataset, (b) random initial cluster centroids, (c–f) illustration of running two iterations of k-means. In each iteration, each training example is assigned to the closest cluster centroid; then each cluster centroid is moved to the mean of the points assigned to it.

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.