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Adding a separate application to provide benchmarks between the curre…
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…nt implementation and previous versions of the framework.
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@cesarsouza
cesarsouza committed May 20, 2016
1 parent 4bc2745 commit 347dd92
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37 changes: 37 additions & 0 deletions Tools/Performance/Comparer/Comparer.sln
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14 changes: 14 additions & 0 deletions Tools/Performance/Comparer/CurrentVersion/App.config
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153 changes: 153 additions & 0 deletions Tools/Performance/Comparer/CurrentVersion/CurrentVersion.csproj
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72 changes: 72 additions & 0 deletions Tools/Performance/Comparer/CurrentVersion/KernelSupportVectorMachineTest.cs
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using Accord.MachineLearning.VectorMachines;
using Accord.MachineLearning.VectorMachines.Learning;
using Accord.Statistics.Kernels;
using BenchmarkDotNet.Attributes;
using System.Text;
using System.Threading.Tasks;
using Accord.Math;
using Accord.Math.Distances;
using Accord.Statistics.Distributions.Univariate;
using Accord;
using Shared;

namespace CurrentVersion
{
[Config(typeof(FastAndDirtyConfig))]
public class KernelSupportVectorMachineTest
{
private readonly double[][] inputs;
private readonly int[] outputs;

SupportVectorMachine<Polynomial> ksvm;
SequentialMinimalOptimization<Polynomial> smo;

public KernelSupportVectorMachineTest()
{
var data = Shared.Examples.YinYang();
inputs = data.Training.Inputs;
outputs = data.Training.Output;
}

[Setup]
public void Setup()
{
ksvm = new SupportVectorMachine<Polynomial>(inputs: 2, kernel: new Polynomial(2));
smo = new SequentialMinimalOptimization<Polynomial>()
{
Model = ksvm
};
}

[Benchmark]
public IntRange Accord_Core()
{
return new IntRange(0, 1);
}

[Benchmark]
public Cosine Accord_Math()
{
return new Cosine();
}

[Benchmark]
public NormalDistribution Accord_Statistics()
{
return new NormalDistribution();
}

[Benchmark]
public SupportVectorMachine<Polynomial> v3_1_0()
{
ksvm = new SupportVectorMachine<Polynomial>(inputs: 2, kernel: new Polynomial(2));
smo = new SequentialMinimalOptimization<Polynomial>()
{
Model = ksvm
};
smo.Learn(inputs, outputs);
return ksvm;
}

}
}
74 changes: 74 additions & 0 deletions Tools/Performance/Comparer/CurrentVersion/MulticlassSupportVectorMachineTest.cs
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using Accord.MachineLearning.VectorMachines;
using Accord.MachineLearning.VectorMachines.Learning;
using Accord.Statistics.Kernels;
using BenchmarkDotNet.Attributes;
using System.Text;
using System.Threading.Tasks;
using Accord.Math;
using Accord.Math.Distances;
using Accord.Statistics.Distributions.Univariate;
using Accord;
using Shared;

namespace CurrentVersion
{
[Config(typeof(FastAndDirtyConfig))]
public class MulticlassSupportVectorMachineTest
{
private readonly Problem problem;

MulticlassSupportVectorMachine<Polynomial> ksvm;
MulticlassSupportVectorLearning<Polynomial> smo;

public MulticlassSupportVectorMachineTest()
{
problem = Shared.Examples.KaggleDigits();
}

[Setup]
public void Setup()
{
ksvm = new MulticlassSupportVectorMachine<Polynomial>(
inputs: 2, kernel: new Polynomial(2), classes: 10);

smo = new MulticlassSupportVectorLearning<Polynomial>()
{
Model = ksvm
};
}

[Benchmark]
public IntRange Accord_Core()
{
return new IntRange(0, 1);
}

[Benchmark]
public Cosine Accord_Math()
{
return new Cosine();
}

[Benchmark]
public NormalDistribution Accord_Statistics()
{
return new NormalDistribution();
}

[Benchmark]
public MulticlassSupportVectorMachine<Polynomial> v3_1_0()
{
ksvm = new MulticlassSupportVectorMachine<Polynomial>(
inputs: 2, kernel: new Polynomial(2), classes: 10);

smo = new MulticlassSupportVectorLearning<Polynomial>()
{
Model = ksvm
};

smo.Learn(problem.Training.Inputs, problem.Testing.Output);
return ksvm;
}

}
}
26 changes: 26 additions & 0 deletions Tools/Performance/Comparer/CurrentVersion/Program.cs
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using Accord.Statistics.Kernels;
using BenchmarkDotNet.Attributes;
using BenchmarkDotNet.Configs;
using BenchmarkDotNet.Jobs;
using BenchmarkDotNet.Running;
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;

namespace CurrentVersion
{
class Program
{
static void Main(string[] args)
{
BenchmarkRunner.Run<KernelSupportVectorMachineTest>();
BenchmarkRunner.Run<MulticlassSupportVectorMachineTest>();
//MulticlassSupportVectorMachineTest().v3_1_0();
//Console.ReadLine();
}


}
}
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