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  2. MongoDB - Wikipedia

    en.wikipedia.org/wiki/MongoDB

    MongoDB provides three ways to perform aggregation: the aggregation pipeline, the map-reduce function and single-purpose aggregation methods. [40] Map-reduce can be used for batch processing of data and aggregation operations. However, according to MongoDB's documentation, the aggregation pipeline provides better performance for most ...

  3. MapReduce - Wikipedia

    en.wikipedia.org/wiki/MapReduce

    MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...

  4. Aggregate (data warehouse) - Wikipedia

    en.wikipedia.org/wiki/Aggregate_(data_warehouse)

    An aggregate is a type of summary used in dimensional models of data warehouses to shorten the time it takes to provide answers to typical queries on large sets of data. The reason why aggregates can make such a dramatic increase in the performance of a data warehouse is the reduction of the number of rows to be accessed when responding to a query.

  5. Cartographic generalization - Wikipedia

    en.wikipedia.org/wiki/Cartographic_generalization

    During the first half of the 20th century, cartographers began to think seriously about how the features they drew depended on scale. Eduard Imhof, one of the most accomplished academic and professional cartographers at the time, published a study of city plans on maps at a variety of scales in 1937, itemizing several forms of generalization that occurred, including those later termed ...

  6. Maximum a posteriori estimation - Wikipedia

    en.wikipedia.org/wiki/Maximum_a_posteriori...

    The MAP can be used to obtain a point estimate of an unobserved quantity on the basis of empirical data. It is closely related to the method of maximum likelihood (ML) estimation, but employs an augmented optimization objective which incorporates a prior density over the quantity one wants to estimate.

  7. Aggregate data - Wikipedia

    en.wikipedia.org/wiki/Aggregate_data

    Aggregate data are also used for medical and educational purposes. Aggregate data is widely used, but it also has some limitations, including drawing inaccurate inferences and false conclusions which is also termed ‘ecological fallacy’. [3] ‘Ecological fallacy’ means that it is invalid for users to draw conclusions on the ecological ...

  8. Bootstrap aggregating - Wikipedia

    en.wikipedia.org/wiki/Bootstrap_aggregating

    Bootstrap aggregating, also called bagging (from bootstrap aggregating) or bootstrapping, is a machine learning (ML) ensemble meta-algorithm designed to improve the stability and accuracy of ML classification and regression algorithms.

  9. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity.