GiveAGap 1.0.3

C# Library to perfrom Variable Selection according to the Give-A-Gap algortithm.

Install-Package GiveAGap -Version 1.0.3
dotnet add package GiveAGap --version 1.0.3
<PackageReference Include="GiveAGap" Version="1.0.3" />
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add GiveAGap --version 1.0.3
The NuGet Team does not provide support for this client. Please contact its maintainers for support.

Headings
Install the package and then add at least this line of code below to run once the algorithm
Code Block
var mutationProb = 0.1f;
var crossOverProb = 0.8f;
var dimVincoli = 1000;
var dimVars = 15;
var trPerc = 0.5;
var vdPerc = 0.25;
var myTest = new SynthTest(dimVincoli, dimVars, trPerc, vdPerc, 1, 1); // or Create another test expanding SynthTest.cs
GeneticAlgorithmSETUP setup = new GeneticAlgorithmSETUP(myTest, dimVincoli, dimVars, trPerc, vdPerc, 1, crossOverProb, mutationProb);
setup.minFit = 0.45;
setup.forcedINOUT = Vector<double>.Build.Dense(setup.dimVars); // modify your ForcedInOutClass
var forcedINOUT = setup.forcedINOUT;
var result = setup.Start(0.8,30,true); // Termination Conditions (minFit,minGen,and)
Console.WriteLine("SELECTED: " + result.Item1);
Console.WriteLine("In " + result.Item2 + " generations");
Console.WriteLine("In " + result.Item3 + " seconds");
Console.WriteLine("Fitness on TS " + result.Item4);
Console.WriteLine("Fitness on TR VD " + result.Item5);
Console.WriteLine("*****************");
Explaination
Basically you need to choose mutation and crossover probability, then setup the algorithm giving him the size of the input Matrix, and then calling setup.Start() the algorithm starts and when execution finishes you get a tuple with all element you need for the analysis

Headings
Install the package and then add at least this line of code below to run once the algorithm
Code Block
var mutationProb = 0.1f;
var crossOverProb = 0.8f;
var dimVincoli = 1000;
var dimVars = 15;
var trPerc = 0.5;
var vdPerc = 0.25;
var myTest = new SynthTest(dimVincoli, dimVars, trPerc, vdPerc, 1, 1); // or Create another test expanding SynthTest.cs
GeneticAlgorithmSETUP setup = new GeneticAlgorithmSETUP(myTest, dimVincoli, dimVars, trPerc, vdPerc, 1, crossOverProb, mutationProb);
setup.minFit = 0.45;
setup.forcedINOUT = Vector<double>.Build.Dense(setup.dimVars); // modify your ForcedInOutClass
var forcedINOUT = setup.forcedINOUT;
var result = setup.Start(0.8,30,true); // Termination Conditions (minFit,minGen,and)
Console.WriteLine("SELECTED: " + result.Item1);
Console.WriteLine("In " + result.Item2 + " generations");
Console.WriteLine("In " + result.Item3 + " seconds");
Console.WriteLine("Fitness on TS " + result.Item4);
Console.WriteLine("Fitness on TR VD " + result.Item5);
Console.WriteLine("*****************");
Explaination
Basically you need to choose mutation and crossover probability, then setup the algorithm giving him the size of the input Matrix, and then calling setup.Start() the algorithm starts and when execution finishes you get a tuple with all element you need for the analysis

Dependencies

This package has no dependencies.

This package is not used by any popular GitHub repositories.

Version History

Version Downloads Last updated
1.0.3 271 11/11/2017
1.0.2 271 11/5/2017
1.0.1 236 11/5/2017
1.0.0 280 11/5/2017