enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  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. Biclustering - Wikipedia

    en.wikipedia.org/wiki/Biclustering

    Biclustering, block clustering, [1] [2] Co-clustering or two-mode clustering [3] [4] [5] is a data mining technique which allows simultaneous clustering of the rows and columns of a matrix. The term was first introduced by Boris Mirkin [ 6 ] to name a technique introduced many years earlier, [ 6 ] in 1972, by John A. Hartigan .

  4. Error recovery control - Wikipedia

    en.wikipedia.org/wiki/Error_recovery_control

    Modern hard drives feature an ability to recover from some read/write errors by internally remapping sectors and performing other forms of self-test and recovery. The process for this can sometimes take several seconds or (under heavy usage) minutes, during which time the drive is unresponsive.

  5. 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]

  6. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    More precisely, if one plots the percentage of variance explained by the clusters against the number of clusters, the first clusters will add much information (explain a lot of variance), but at some point the marginal gain will drop, giving an angle in the graph. The number of clusters is chosen at this point, hence the "elbow criterion".

  7. Information bottleneck method - Wikipedia

    en.wikipedia.org/wiki/Information_bottleneck_method

    The information bottleneck method is a technique in information theory introduced by Naftali Tishby, Fernando C. Pereira, and William Bialek. [1] It is designed for finding the best tradeoff between accuracy and complexity (compression) when summarizing (e.g. clustering) a random variable X, given a joint probability distribution p(X,Y) between X and an observed relevant variable Y - and self ...

  8. Western Digital (WDC) Q1 2025 Earnings Call Transcript - AOL

    www.aol.com/western-digital-wdc-q1-2025...

    Image source: The Motley Fool. Western Digital (NASDAQ: WDC) Q1 2025 Earnings Call Oct 24, 2024, 4:30 p.m. ET. Contents: Prepared Remarks. Questions and Answers. Call Participants

  9. Data recovery - Wikipedia

    en.wikipedia.org/wiki/Data_recovery

    The most common data recovery scenarios involve an operating system failure, malfunction of a storage device, logical failure of storage devices, accidental damage or deletion, etc. (typically, on a single-drive, single-partition, single-OS system), in which case the ultimate goal is simply to copy all important files from the damaged media to another new drive.