private InputLayer InicializarModeloVisualizer()
{
var inputLayer = new InputLayer("Input");
var sepalLengthInput = new Input("Sepal Length");
var SepalWidthInput = new Input("Sepal Width");
var PetalLengthInput = new Input("PetalLength");
var PetalWidthInput = new Input("Petal Width");
inputLayer.AddNode(sepalLengthInput);
inputLayer.AddNode(SepalWidthInput);
inputLayer.AddNode(PetalLengthInput);
inputLayer.AddNode(PetalWidthInput);
inputLayer.Bias = new Bias("Bias Input")
{
OutputValue = 1.0
};
var capaOculta = new PerceptronLayer("Oculta");
var cantNeuronasOcultas = (int)spinNeuronasOculta.Value;
var funcionActivacion = (cboFuncionActivacionOculta.SelectedItem as EnumInfo <ActivationType>).Valor.Map();
for (int i = 0; i < cantNeuronasOcultas; i++)
{
var neurona = new Perceptron("oculta" + i)
{
ActivationFunction = funcionActivacion
};
capaOculta.AddNode(neurona);
}
capaOculta.Bias = new Bias("Bias Oculta")
{
OutputValue = 1.0
};
inputLayer.Connect(capaOculta);
funcionActivacion = (cboFuncionActivacionSalida.SelectedItem as EnumInfo <ActivationType>).Valor.Map();
var setosaOutput = new Perceptron("Setosa")
{
ActivationFunction = funcionActivacion
};
var versicolorOutput = new Perceptron("Versicolor")
{
ActivationFunction = funcionActivacion
};
var virginicaOutput = new Perceptron("Virginica")
{
ActivationFunction = funcionActivacion
};
var capaSalida = new PerceptronLayer("Salida");
capaSalida.AddNode(setosaOutput);
capaSalida.AddNode(versicolorOutput);
capaSalida.AddNode(virginicaOutput);
capaOculta.Connect(capaSalida);
return(inputLayer);
}
private void btnStart_Click(object sender, EventArgs e)
{
_input = new InputLayer("Input")
{
Bias = new Bias("bias")
{
OutputValue = 1.234
}
};
_input.AddNode(new Input("e1")
{
OutputValue = 0.255
});
_input.AddNode(new Input("e2")
{
OutputValue = 0.455
});
_input.AddNode(new Input("e3")
{
OutputValue = -0.78967656
});
_input.AddNode(new Input("e4")
{
OutputValue = 0.0
});
//_input.AddNode(new Input("e5") { OutputValue = 0.255 });
//_input.AddNode(new Input("e6") { OutputValue = 0.455 });
//_input.AddNode(new Input("e7") { OutputValue = -0.78967656 });
//_input.AddNode(new Input("e8") { OutputValue = 0.011 });
//_input.AddNode(new Input("e9") { OutputValue = 0.2255 });
//_input.AddNode(new Input("e10") { OutputValue = 43.455 });
//_input.AddNode(new Input("e11") { OutputValue = -11.67656 });
//_input.AddNode(new Input("e12") { OutputValue = -1.001 });
var hidden = new PerceptronLayer("Hidden");
hidden.AddNode(new Perceptron("o1")
{
ActivationFunction = ActivationFunction.BinaryStep, OutputValue = 2.364, SumValue = 2.364
});
hidden.AddNode(new Perceptron("o2")
{
ActivationFunction = ActivationFunction.LeakyRelu, OutputValue = -0.552, SumValue = 55.44
});
hidden.AddNode(new Perceptron("o4")
{
ActivationFunction = ActivationFunction.Relu, OutputValue = 1.324, SumValue = 4.34
});
//hidden.AddNode(new Perceptron("o3") { ActivationFunction = ActivationFunction.Linear, OutputValue = 0.0, SumValue = 19.22 });
//hidden.AddNode(new Perceptron("o5") { ActivationFunction = ActivationFunction.Sigmoid, OutputValue = -0.12, SumValue = 25.224 });
//hidden.AddNode(new Perceptron("o6") { ActivationFunction = ActivationFunction.Tanh, OutputValue = 10.3, SumValue = 1.222 });
_input.Connect(hidden);
var output = new PerceptronLayer("Output");
output.AddNode(new Perceptron("s1")
{
ActivationFunction = ActivationFunction.Softmax, OutputValue = 0.567656, SumValue = 0.454
});
output.AddNode(new Perceptron("s2")
{
ActivationFunction = ActivationFunction.Sigmoid, OutputValue = 0.176545, SumValue = 0.54
});
//output.AddNode(new Perceptron("s3") { ActivationFunction = ActivationFunction.Softmax, OutputValue = 0.9545, SumValue = 0.133 });
//output.AddNode(new Perceptron("s4") { ActivationFunction = ActivationFunction.Softmax, OutputValue = 0.145, SumValue = 0.88 });
hidden.Connect(output);
var aleatorio = new Random(2);
foreach (var p in hidden.Nodes)
{
foreach (var edge in p.Edges)
{
int sign = aleatorio.Next(-1, 2);
edge.Weight = aleatorio.NextDouble() * sign;
}
}
foreach (var p in output.Nodes)
{
foreach (var edge in p.Edges)
{
int sign = aleatorio.Next(-1, 1);
edge.Weight = aleatorio.NextDouble() * sign;
}
}
NeuralNetworkVisualizerControl1.InputLayer = _input;
btnChangeValue.Enabled = btnAddBias.Enabled = btnClear.Enabled = trackZoom.Enabled = cboQuality.Enabled = true;
}