alglib2.dll 3.10.4

.NET Framework
Install-Package alglib2.dll -Version 3.10.4
dotnet add package alglib2.dll --version 3.10.4
<PackageReference Include="alglib2.dll" Version="3.10.4" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add alglib2.dll --version 3.10.4
The NuGet Team does not provide support for this client. Please contact its maintainers for support.
#r "nuget: alglib2.dll, 3.10.4"
#r directive can be used in F# Interactive, C# scripting and .NET Interactive. Copy this into the interactive tool or source code of the script to reference the package.
// Install alglib2.dll as a Cake Addin
#addin nuget:?package=alglib2.dll&version=3.10.4

// Install alglib2.dll as a Cake Tool
#tool nuget:?package=alglib2.dll&version=3.10.4
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

ALGLIB is a cross-platform numerical analysis and data processing library. It supports several programming languages (C++, C#, Pascal, VBA) and several operating systems (Windows, Linux, Solaris). ALGLIB features include:

Data analysis (classification/regression, including neural networks)
Optimization and nonlinear solvers
Interpolation and linear/nonlinear least-squares fitting
Linear algebra (direct algorithms, EVD/SVD), direct and iterative linear solvers, Fast Fourier Transform and many other algorithms (numerical integration, ODEs, statistics, special functions)

Product Versions
.NET Framework net
Compatible target framework(s)
Additional computed target framework(s)
Learn more about Target Frameworks and .NET Standard.

This package has no dependencies.

NuGet packages

This package is not used by any NuGet packages.

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Version Downloads Last updated
3.10.4 5,562 10/6/2016
3.10.3 1,118 10/6/2016
3.10.2 841 8/30/2016
3.10.1 801 8/30/2016

CSV import - you can now read 2D matrix from CSV file
AGS (Adaptive Gradient Sampling) algorithm for nonsmooth nonconvex constrained optimization, which makes ALGLIB one of the few commercial packages supporting nonsmooth optimization.
Ward's method for hierarchical clustering
special lightweight linear solvers without condition number estimation and iterative refinement - orders of magnitude faster than their "feature-rich" counterparts
parallel k-means clustering (parallelism is supported only in commercial edition of ALGLIB)