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  2. dplyr - Wikipedia

    en.wikipedia.org/wiki/Dplyr

    dplyr is an R package whose set of functions are designed to enable dataframe (a spreadsheet-like data structure) manipulation in an intuitive, user-friendly way. It is one of the core packages of the popular tidyverse set of packages in the R programming language . [ 1 ]

  3. Normalization (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Normalization_(machine...

    This solves the problem of different features having vastly different scales, for example if one feature is measured in kilometers and another in nanometers. Activation normalization, on the other hand, is specific to deep learning , and includes methods that rescale the activation of hidden neurons inside neural networks .

  4. List of NP-complete problems - Wikipedia

    en.wikipedia.org/wiki/List_of_NP-complete_problems

    The problem for graphs is NP-complete if the edge lengths are assumed integers. The problem for points on the plane is NP-complete with the discretized Euclidean metric and rectilinear metric. The problem is known to be NP-hard with the (non-discretized) Euclidean metric. [3]: ND22, ND23

  5. Canonicalization - Wikipedia

    en.wikipedia.org/wiki/Canonicalization

    In computer science, canonicalization (sometimes standardization or normalization) is a process for converting data that has more than one possible representation into a "standard", "normal", or canonical form.

  6. Canonical form - Wikipedia

    en.wikipedia.org/wiki/Canonical_form

    For example, polynomials are conventionally written with the terms in descending powers: it is more usual to write x 2 + x + 30 than x + 30 + x 2, although the two forms define the same polynomial. By contrast, the existence of Jordan canonical form for a matrix is a deep theorem.

  7. Regularization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Regularization_(mathematics)

    This includes, for example, early stopping, using a robust loss function, and discarding outliers. Implicit regularization is essentially ubiquitous in modern machine learning approaches, including stochastic gradient descent for training deep neural networks , and ensemble methods (such as random forests and gradient boosted trees ).

  8. Normalisation by evaluation - Wikipedia

    en.wikipedia.org/wiki/Normalisation_by_evaluation

    And if the datatype of normal forms is typed, the type of reify (and therefore of nbe) then makes it clear that normalization is type preserving. [ 9 ] Normalization by evaluation also scales to the simply typed lambda calculus with sums ( + ), [ 7 ] using the delimited control operators shift and reset .

  9. Sixth normal form - Wikipedia

    en.wikipedia.org/wiki/Sixth_normal_form

    The sixth normal form is currently as of 2009 being used in some data warehouses where the benefits outweigh the drawbacks, [9] for example using anchor modeling.Although using 6NF leads to an explosion of tables, modern databases can prune the tables from select queries (using a process called 'table elimination' - so that a query can be solved without even reading some of the tables that the ...