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  2. Agnostic (data) - Wikipedia

    en.wikipedia.org/wiki/Agnostic_(data)

    This is a non data-agnostic method, as it uses a specified file type, downloaded from a specific location, and does not function unless those requirements are met. Non data-agnostic devices and programs can present problems.

  3. Non-negative matrix factorization - Wikipedia

    en.wikipedia.org/wiki/Non-negative_matrix...

    Non-negative matrix factorization (NMF or NNMF), also non-negative matrix approximation [1] [2] is a group of algorithms in multivariate analysis and linear algebra where a matrix V is factorized into (usually) two matrices W and H, with the property that all three matrices have no negative elements. This non-negativity makes the resulting ...

  4. Schema-agnostic databases - Wikipedia

    en.wikipedia.org/wiki/Schema-agnostic_Databases

    The evolution of databases in the direction of heterogeneous data environments strongly impacts the usability, semiotics and semantic assumptions behind existing data accessibility methods such as structured queries, keyword-based search and visual query systems. With schema-less databases containing potentially millions of dynamically changing ...

  5. Meta-learning (computer science) - Wikipedia

    en.wikipedia.org/wiki/Meta-learning_(computer...

    Meta-learning [1] [2] is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of 2017, the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to improve the performance of existing ...

  6. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]

  7. Non-personal data - Wikipedia

    en.wikipedia.org/wiki/Non-personal_data

    Non-Personal Data (NPD) is electronic data that does not contain any information that can be used to identify a natural person.Thus, it can either be data that has no personal information to begin with (such as weather data, stock prices, data from anonymous IoT sensors); or it is data that had personal data that was subsequently pseudoanonymized (for example, identifiable strings substituted ...

  8. Nondeterministic algorithm - Wikipedia

    en.wikipedia.org/wiki/Nondeterministic_algorithm

    Algorithms of this sort are used to define complexity classes based on nondeterministic time and nondeterministic space complexity. They may be simulated using nondeterministic programming, a method for specifying nondeterministic algorithms and searching for the choices that lead to a correct run, often using a backtracking search.

  9. Data striping - Wikipedia

    en.wikipedia.org/wiki/Data_striping

    The amount of data in one stride multiplied by the number of data disks in the array (i.e., stripe depth times stripe width, which in the geometrical analogy would yield an area) is sometimes called the stripe size or stripe width. [5] Wide striping occurs when chunks of data are spread across multiple arrays, possibly all the drives in the system.