the K-means clustering algorithm produces :
• A final estimate of cluster *** (i.e. their ***)
• An assignment of each point to their respective ***
the K-means clustering algorithm produces :
• A final estimate of cluster centroids (i.e. their coordinates)
• An assignment of each point to their respective cluster
the K-means clustering algorithm produces :
• A final estimate of cluster *** (i.e. their ***)
• An assignment of each point to their respective ***
the K-means clustering algorithm produces :
• A final estimate of cluster *** (i.e. their ***)
• An assignment of each point to their respective ***
the K-means clustering algorithm produces :
• A final estimate of cluster centroids (i.e. their coordinates)
• An assignment of each point to their respective cluster
status | not learned | measured difficulty | 37% [default] | last interval [days] | |||
---|---|---|---|---|---|---|---|
repetition number in this series | 0 | memorised on | scheduled repetition | ||||
scheduled repetition interval | last repetition or drill |