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  2. Calinski–Harabasz index - Wikipedia

    en.wikipedia.org/wiki/Calinski–Harabasz_index

    where n i is the number of points in cluster C i, c i is the centroid of C i, and c is the overall centroid of the data. BCSS measures how well the clusters are separated from each other (the higher the better). WCSS (Within-Cluster Sum of Squares) is the sum of squared Euclidean distances between the data points and their respective cluster ...

  3. Key clustering - Wikipedia

    en.wikipedia.org/wiki/Key_clustering

    Key or hash function should avoid clustering, the mapping of two or more keys to consecutive slots. Such clustering may cause the lookup cost to skyrocket, even if the load factor is low and collisions are infrequent. The popular multiplicative hash [1] is claimed to have particularly poor clustering behaviour. [2]

  4. Hash table - Wikipedia

    en.wikipedia.org/wiki/Hash_table

    On the other hand, some hashing algorithms prefer to have the size be a prime number. [18] For open addressing schemes, the hash function should also avoid clustering, the mapping of two or more keys to consecutive slots. Such clustering may cause the lookup cost to skyrocket, even if the load factor is low and collisions are infrequent.

  5. Primary clustering - Wikipedia

    en.wikipedia.org/wiki/Primary_clustering

    In computer programming, primary clustering is a phenomenon that causes performance degradation in linear-probing hash tables.The phenomenon states that, as elements are added to a linear probing hash table, they have a tendency to cluster together into long runs (i.e., long contiguous regions of the hash table that contain no free slots).

  6. Automatic clustering algorithms - Wikipedia

    en.wikipedia.org/wiki/Automatic_Clustering...

    BIRCH (balanced iterative reducing and clustering using hierarchies) is an algorithm used to perform connectivity-based clustering for large data-sets. [7] It is regarded as one of the fastest clustering algorithms, but it is limited because it requires the number of clusters as an input.

  7. James G. Andress - Pay Pals - The Huffington Post

    data.huffingtonpost.com/paypals/james-g-andress

    From January 2008 to March 2008, if you bought shares in companies when James G. Andress joined the board, and sold them when he left, you would have a -8.4 percent return on your investment, compared to a -9.3 percent return from the S&P 500.

  8. Alfred F. Kelly, Jr. - Pay Pals - The Huffington Post

    data.huffingtonpost.com/paypals/alfred-f-kelly-jr

    From June 2009 to December 2012, if you bought shares in companies when Alfred F. Kelly, Jr. joined the board, and sold them when he left, you would have a 12.1 percent return on your investment, compared to a 59.3 percent return from the S&P 500.

  9. Database index - Wikipedia

    en.wikipedia.org/wiki/Database_index

    This may improve the joins of these tables on the cluster key, since the matching records are stored together and less I/O is required to locate them. [2] The cluster configuration defines the data layout in the tables that are parts of the cluster. A cluster can be keyed with a B-tree index or a hash table. The data block where the table ...