cs-ensembles 1.0.2

dotnet add package cs-ensembles --version 1.0.2                
NuGet\Install-Package cs-ensembles -Version 1.0.2                
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="cs-ensembles" Version="1.0.2" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add cs-ensembles --version 1.0.2                
#r "nuget: cs-ensembles, 1.0.2"                
#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.
// Install cs-ensembles as a Cake Addin
#addin nuget:?package=cs-ensembles&version=1.0.2

// Install cs-ensembles as a Cake Tool
#tool nuget:?package=cs-ensembles&version=1.0.2                

cs-ensembles

Ensembles method implemented in C#

Install

Install-Package cs-ensembles

Usage

The sample codes below show how to use the AdaBoosting classifier:

IEnumerable<DDataRecord<string>> training_sample = LoadTrainingSamples();
IEnumerable<DDataRecord<string>> testing_sample = LoadTestingSamples();

AdaBoost<DDataRecord, string> classifier = new AdaBoost<DDataRecord, string>();
classifier.CreateAndTrainWeakClassifiers(training_sample, (t)=>
{
 //create and return a weak classifier such as a decision tree or perceptron
});
classifier.Train(training_sample);

foreach(DDataRecord rec in testing_sample)
{
   string predicted_label = classifier.Predict(rec);
}

The sample codes below show how to use the TreeBagging classifier:

IEnumerable<DDataRecord<string>> training_sample = LoadTrainingSamples();
IEnumerable<DDataRecord<string>> testing_sample = LoadTestingSamples();

TreeBagging<DDataRecord, string> classifier = new TreeBagging<DDataRecord, string>(
(t)=>
{
  //create and return a classifier such as a decision tree or perceptron
}, 900, 2.0 / 3);
classifier.Train(training_sample);

foreach(DDataRecord rec in testing_sample)
{
    string predicted_label = classifier.Predict(rec);
} 
Product Compatible and additional computed target framework versions.
.NET Framework net461 is compatible.  net462 was computed.  net463 was computed.  net47 was computed.  net471 was computed.  net472 was computed.  net48 was computed.  net481 was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

This package has no dependencies.

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
1.0.2 1,152 5/2/2018
1.0.1 992 5/2/2018

Tree Ensemble Algorithms such as TreeBagging and AdaBoosting in .NET 4.6.1