public void Training(Regression training_data, int batch_size = 128)
{
if (batch_size <= 0)
{
return;
}
if (batch_size > training_data.Length)
{
batch_size = training_data.Length;
}
circle = 0;
do
{
total_error = 0f;
var batch_counter = 0;
var batch_limit = batch_size;
while (batch_counter < training_data.Length)
{
var batch_regression = new Regression();
for (var i = batch_counter; i < batch_limit && i < training_data.Length; i++)
{
batch_regression.Add(training_data.inputs[i], training_data.outputs[i]);
}
var len = batch_regression.Length;
for (var i = 0; i < len; i++)
{
Training(batch_regression.inputs[i], batch_regression.outputs[i]);
total_error += GetError();
}
batch_counter += batch_size;
batch_limit += batch_size;
batch_regression.Dispose();
}
if (!infinite_loop)
{
if (circle >= max_circle)
{
break;
}
}
circle++;
} while (!ignore_error && (total_error >= error_limit));
}