public void CreateSolver(string name, models.Task task)
{
int layers = 2 + HiddenLayers.Count;
int[] neurons = new int[layers];
bool[] delays = new bool[layers - 1];
string[] afs = new string[layers - 1];
neurons[0] = InputNeuronsCount;
for (int i = 1; i < layers - 1; i++)
{
neurons[i] = HiddenLayers[i - 1].NeuronsCount;
}
neurons[layers - 1] = OutputLayer.NeuronsCount;
for (int i = 0; i < layers - 2; i++)
{
delays[i] = HiddenLayers[i].IsUsingW0;
afs[i] = HiddenLayers[i].SelectedAF;
}
delays[layers - 2] = OutputLayer.IsUsingW0;
afs[layers - 2] = OutputLayer.SelectedAF;
PerceptronTopology t = new PerceptronTopology(layers, neurons, delays, afs);
TaskSolver ts = new TaskSolver()
{
Name = name,
TypeName = "Perceptron",
TaskID = task.ID,
Description = t
};
ts.save();
}
private void importTaskSolver(ArchiveTaskSolver archSolver, int taskId)
{
TaskSolver solver = new TaskSolver(archSolver);
solver.TaskID = taskId;
solver.save();
archSolver.ID = solver.ID;
}
public void CreateSolver(string name, models.Task task)
{
InputLayer input = new InputLayer
{
NeuronsCount = InputNeuronsCount,
ForwardConnection = InputLayerAC
};
var layers = new List <WardLayer>();
for (int i = 0; i < HiddenLayers.Count; i++)
{
var groups = new List <NeuronsGroup>();
for (int j = 0; j < HiddenLayers[i].Groups.Count; j++)
{
groups.Add(new NeuronsGroup
{
NeuronsCount = HiddenLayers[i].Groups[j].NeuronsCount,
ActivationFunction = HiddenLayers[i].Groups[j].SelectedAF,
HasDelay = HiddenLayers[i].Groups[j].IsUsingW0
});
}
layers.Add(new WardLayer
{
ForwardConnection = HiddenLayers[i].AC,
Groups = groups
});
}
var groupsOutput = new List <NeuronsGroup>();
for (int j = 0; j < OutputLayer.Groups.Count; j++)
{
groupsOutput.Add(new NeuronsGroup
{
NeuronsCount = OutputLayer.Groups[j].NeuronsCount,
ActivationFunction = OutputLayer.Groups[j].SelectedAF,
HasDelay = OutputLayer.Groups[j].IsUsingW0
});
}
layers.Add(new WardLayer
{
ForwardConnection = OutputLayer.AC,
Groups = groupsOutput
});
WardNNTopology wnn = new WardNNTopology(input, layers);
TaskSolver ts = new TaskSolver()
{
Name = name,
TypeName = "WardNN",
TaskID = task.ID,
Description = wnn
};
ts.save();
}
public void CreateSolver(string name, models.Task task)
{
KohonenNNTopology t = new KohonenNNTopology(Inputs, Outputs,
Width, Height, float.Parse(ClassEps),
SelectedInitializer, SelectedMetric);
TaskSolver solver = new TaskSolver()
{
Name = name,
TaskID = task.ID,
Description = t,
TypeName = "KohonenNet"
};
solver.save();
}
public void CreateSolver(string name, models.Task task)
{
int depth = MaxTreeDepth;
//WARNING!!!
//Here must be selected task template
//and number of inputs and outputs in it.
TreeDescription td = new TreeDescription(Inputs, Outputs, depth);
TaskSolver ts = new TaskSolver()
{
Name = name,
TypeName = "DecisionTreeCART",
TaskID = task.ID,
Description = td
};
ts.save();
}
public void CreateSolver(string name, models.Task task)
{
var layers = new List <ILayer>();
foreach (ConvNNLayerViewModel layerVM in Layers)
{
layers.Add(layerVM.LayerParameters.LayerModel);
}
var t = new ConvNNTopology(InputWidth, InputHeight, InputDepth, layers);
TaskSolver ts = new TaskSolver()
{
Name = name,
TypeName = "ConvNN",
TaskID = task.ID,
Description = t
};
ts.save();
}