private void checkBox1_CheckedChanged(object sender, EventArgs e)
{
if (checkBox1.Checked)
{
checkBox1.Text = "Stop";
}
else
{
checkBox1.Text = "Start";
}
Pattern p = new Pattern();
Random rnd = new Random();
int iRnd;
int i = 0;
double[] target = new double[10];
while (checkBox1.Checked)
{
i++;
iRnd = rnd.Next(0, 60000);
TrainBaseMemStream.loadPattern(iRnd, p);
for (int j = 0; j < 10; j++)
{
target[j] = 0;
}
target[p.val] = 1;
nNet.train(p.data, target);
if (i % 50 == 0)
{
this.Text = nNet.trainCount.ToString() + "/" + nNet.eta.ToString() + "/" + i.ToString();
Application.DoEvents();
}
}
}
/**
* train the dataset
* with "train" method on neuron network library, it takes 2 arguments:
* dataset inputs and dataset targets as an array
*
* */
void train()
{
for (int i = 0; i < 10; i++)
{
foreach (var data in list)
{
nn.train(data.inputs, data.targets);
}
}
data_test();
}
void train()
{
data = new Dataset
{
inputs = new float[] { 0, 0 },
targets = new float[] { 0 },
};
data1 = new Dataset
{
inputs = new float[] { 0, 1 },
targets = new float[] { 1 },
};
data2 = new Dataset
{
inputs = new float[] { 1, 0 },
targets = new float[] { 1 },
};
data3 = new Dataset
{
inputs = new float[] { 1, 1 },
targets = new float[] { 0 },
};
list.Add(data);
list.Add(data1);
list.Add(data2);
list.Add(data3);
for (int i = 0; i < 20; i++)
{
foreach (var data in list)
{
nn.train(data.inputs, data.targets);
}
}
trainTime++;
data_test();
}
