Info
Version: | 0.2.0 |
Author(s): | Sergey Zyuzin |
Last Update: | Friday, September 27, 2013 |
.NET Fiddle: | Create the first Fiddle |
Project Url: | https://github.com/foreverzet/Sharpkit.Learn |
NuGet Url: | https://www.nuget.org/packages/Sharpkit.Learn |
Install
Install-Package Sharpkit.Learn
dotnet add package Sharpkit.Learn
paket add Sharpkit.Learn
Sharpkit.Learn Download (Unzip the "nupkg" after downloading)
Dependencies
- MathNet.Numerics(2.6.1)
Tags
Currently has Linear Regression, Logistic Regression, Ridge Regression/Classifier, Svm classifier.
Initially it is port of popular Scikit-learn machine learning python library and has very close design.
Sharpkit.Learn is based on the state of the art algorithm implementations and uses liblinear, libsvm, Math.Net
etc.
Various BLAS providers like MKL can be used to speed up the computation. Both dense and sparse matrices
are supported.