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In statistics, kernel Fisher discriminant analysis (KFD), [1] also known as generalized discriminant analysis [2] and kernel discriminant analysis, [3] is a kernelized version of linear discriminant analysis (LDA). It is named after Ronald Fisher.
ML.NET is a free software machine learning library for the C# programming language. [3] [4] The NAG Library has C# API. Commercially licensed. NMath by CenterSpace Software: Commercial numerical component libraries for the .NET platform, including signal processing (FFT) classes, a linear algebra (LAPACK & BLAS) framework, and a statistics package.
Math.NET Numerics started 2009 by merging code and teams of dnAnalytics with Math.NET Iridium. It is influenced by ALGLIB, JAMA and Boost, among others, and has accepted numerous code contributions. [1] [2] It is part of the Math.NET initiative to build and maintain open mathematical toolkits for the .NET platform since 2002. [citation needed]
Intel oneAPI Math Kernel Library (Intel oneMKL) , formerly known as Intel Math Kernel Library, is a library of optimized math routines for science, engineering, and financial applications. Core math functions include BLAS , LAPACK , ScaLAPACK , sparse solvers, fast Fourier transforms , and vector math.
The kernel of a m × n matrix A over a field K is a linear subspace of K n. That is, the kernel of A, the set Null(A), has the following three properties: Null(A) always contains the zero vector, since A0 = 0. If x ∈ Null(A) and y ∈ Null(A), then x + y ∈ Null(A). This follows from the distributivity of matrix multiplication over addition.
C# 2009 5.0.0 / 04.2022 Free MIT License: C# numerical analysis library with linear algebra support Matrix Template Library: Jeremy Siek, Peter Gottschling, Andrew Lumsdaine, et al. C++ 1998 4.0 / 2018 Free Boost Software License High-performance C++ linear algebra library based on Generic programming: NAG Numerical Library: The Numerical ...
The 9-person Symbolab team, based in Tel Aviv, will join Course Hero . The platforms will live under independent branding for the near future, according to Andrew Grauer, CEO of Course Hero.
In machine learning, kernel machines are a class of algorithms for pattern analysis, whose best known member is the support-vector machine (SVM). These methods involve using linear classifiers to solve nonlinear problems. [1]