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Ignore:
Timestamp:
02/01/17 09:58:06 (8 years ago)
Author:
gkronber
Message:

#2288: introduced base class for variable network instance description and implemented GRR and Linear variable networks as specific classes

File:
1 edited

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  • trunk/sources/HeuristicLab.Problems.Instances.DataAnalysis/3.3/Regression/VariableNetworks/VariableNetworkInstanceProvider.cs

    r14260 r14630  
    4949    public override IEnumerable<IDataDescriptor> GetDataDescriptors() {
    5050      var numVariables = new int[] { 10, 20, 50, 100 };
    51       var noiseRatios = new double[] { 0, 0.01, 0.05, 0.1 };
     51      var noiseRatios = new double[] { 0, 0.01, 0.05, 0.1, 0.2 };
    5252      var rand = new MersenneTwister((uint)Seed); // use fixed seed for deterministic problem generation
    53       return (from size in numVariables
    54               from noiseRatio in noiseRatios
    55               select new VariableNetwork(size, noiseRatio, new MersenneTwister((uint)rand.Next())))
    56               .Cast<IDataDescriptor>()
    57               .ToList();
     53      var lr = (from size in numVariables
     54                from noiseRatio in noiseRatios
     55                select new LinearVariableNetwork(size, noiseRatio, new MersenneTwister((uint)rand.Next())))
     56                .Cast<IDataDescriptor>()
     57                .ToList();
     58      var gp = (from size in numVariables
     59                from noiseRatio in noiseRatios
     60                select new GaussianProcessVariableNetwork(size, noiseRatio, new MersenneTwister((uint)rand.Next())))
     61                .Cast<IDataDescriptor>()
     62                .ToList();
     63      return lr.Concat(gp);
    5864    }
    5965
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