FLearn 2.1.2

.NET 7.0 This package targets .NET 7.0. The package is compatible with this framework or higher. 
dotnet add package FLearn --version 2.1.2
                    


                    

                
NuGet\Install-Package FLearn -Version 2.1.2
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package. 
<PackageReference Include="FLearn" Version="2.1.2" />
For projects that support PackageReference, copy this XML node into the project file to reference the package. 
<PackageVersion Include="FLearn" Version="2.1.2" />
                    


                            Directory.Packages.props
                        

                    

                
<PackageReference Include="FLearn" />
                    


                            Project file
For projects that support Central Package Management (CPM), copy this XML node into the solution Directory.Packages.props file to version the package. 
paket add FLearn --version 2.1.2
                    


                    

                
#r "nuget: FLearn, 2.1.2"
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package. 
#:package FLearn@2.1.2
#:package directive can be used in C# file-based apps starting in .NET 10 preview 4. Copy this into a .cs file before any lines of code to reference the package. 
#addin nuget:?package=FLearn&version=2.1.2
                    


                            Install as a Cake Addin
                        

                    

                
#tool nuget:?package=FLearn&version=2.1.2
                    


                            Install as a Cake Tool

FLearn

  1. To learn through failure.
  2. A supervised learning library written in F# for F#.

Built on top of the Math.Net Numerics linear algebra library, FLearn offers an extensible, scalable, and interactive take on supervised learning. Utilizing tools from online convex optimization, FLearn provides a framework for specifying and optimizing various predictive models. Straight out of the box you can:

  1. Construct predictive models, with statistical and worst-case guarantees, via the minimization of convex loss functions.
  2. Utilize feature maps such as those provided by random Fourier features and the Nystroem method.
  3. Make predictions and estimate their errors. Think error bars and Gaussian processes.
  4. Learn from noisily labeled data via corruption corrected loss functions.

FLearn is both an "online" and a "batch" learning library, that is it can learn from data sequentially as it comes, or learn from a large training set of data in one go. Example usage of the package can be found here.

Product Compatible and additional computed target framework versions.
.NET net7.0 is compatible.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed.  net9.0 was computed.  net9.0-android was computed.  net9.0-browser was computed.  net9.0-ios was computed.  net9.0-maccatalyst was computed.  net9.0-macos was computed.  net9.0-tvos was computed.  net9.0-windows was computed.  net10.0 was computed.  net10.0-android was computed.  net10.0-browser was computed.  net10.0-ios was computed.  net10.0-maccatalyst was computed.  net10.0-macos was computed.  net10.0-tvos was computed.  net10.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

This package is not used by any popular GitHub repositories.

Version Downloads Last Updated
2.1.2 271 9/24/2023
2.1.1 205 9/23/2023
2.1.0 196 9/23/2023
2.0.3.4 198 9/21/2023
2.0.3.3 213 9/20/2023
2.0.3.2 213 9/20/2023
2.0.3.1 216 9/16/2023
2.0.3 186 9/16/2023
2.0.2 124 9/16/2023
2.0.1 220 9/2/2023
2.0.0 510 9/5/2021
1.2.1 995 11/9/2018
1.2.0 1,124 8/18/2018
1.1.3 1,471 2/23/2018
1.1.2 1,438 1/17/2018
1.1.1 1,699 12/29/2017
1.1.0 1,656 12/10/2017
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