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  2. Pyspread - Wikipedia

    en.wikipedia.org/wiki/Pyspread

    Free and open-source software portal; Pyspread is a non-traditional spreadsheet.Cells in pyspread's grid accept expressions in the Python programming language. [2] A cell can return any Python object, which allows calculations with vectors, matrices, fractions, arbitrary precision numbers and symbols.

  3. Comparison of numerical-analysis software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_numerical...

    Interfacing to external modules written in C, Java, Python or other languages. Language syntax similar to MATLAB. Used for numerical computing in engineering and physics.

  4. Least-squares support vector machine - Wikipedia

    en.wikipedia.org/wiki/Least-squares_support...

    Least-squares support-vector machines (LS-SVM) for statistics and in statistical modeling, are least-squares versions of support-vector machines (SVM), which are a set of related supervised learning methods that analyze data and recognize patterns, and which are used for classification and regression analysis.

  5. Vectorization (mathematics) - Wikipedia

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

    Julia has the vec(A) function as well. In Python NumPy arrays implement the flatten method, [ note 1 ] while in R the desired effect can be achieved via the c() or as.vector() functions. In R , function vec() of package 'ks' allows vectorization and function vech() implemented in both packages 'ks' and 'sn' allows half-vectorization.

  6. Vector optimization - Wikipedia

    en.wikipedia.org/wiki/Vector_optimization

    Vector optimization is a subarea of mathematical optimization where optimization problems with a vector-valued objective functions are optimized with respect to a given partial ordering and subject to certain constraints.

  7. Vector-valued function - Wikipedia

    en.wikipedia.org/wiki/Vector-valued_function

    A vector-valued function, also referred to as a vector function, is a mathematical function of one or more variables whose range is a set of multidimensional vectors or infinite-dimensional vectors. The input of a vector-valued function could be a scalar or a vector (that is, the dimension of the domain could be 1 or greater than 1); the ...

  8. Kernel method - Wikipedia

    en.wikipedia.org/wiki/Kernel_method

    For many algorithms that solve these tasks, the data in raw representation have to be explicitly transformed into feature vector representations via a user-specified feature map: in contrast, kernel methods require only a user-specified kernel, i.e., a similarity function over all pairs of data points computed using inner products.

  9. Reduced cost - Wikipedia

    en.wikipedia.org/wiki/Reduced_cost

    Given a system minimize subject to ,, the reduced cost vector can be computed as , where is the dual cost vector. It follows directly that for a minimization problem, any non- basic variables at their lower bounds with strictly negative reduced costs are eligible to enter that basis, while any basic variables must have a reduced cost that is ...